hyperparameter_tuning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hyperparameter Tuning using HyperDrive\n",
    "\n",
    "Import Dependencies. In the cell below, import all the dependencies that you will need to complete the project."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "gather": {
     "logged": 1598531914256
    }
   },
   "outputs": [],
   "source": [
    "from azureml.core import Workspace, Experiment\n",
    "from azureml.core.compute import ComputeTarget, AmlCompute\n",
    "from azureml.core.compute_target import ComputeTargetException\n",
    "from azureml.widgets import RunDetails\n",
    "from azureml.train.sklearn import SKLearn\n",
    "from azureml.train.hyperdrive.run import PrimaryMetricGoal\n",
    "from azureml.train.hyperdrive.policy import BanditPolicy\n",
    "from azureml.train.hyperdrive.sampling import RandomParameterSampling\n",
    "from azureml.train.hyperdrive.runconfig import HyperDriveConfig\n",
    "from azureml.train.hyperdrive.parameter_expressions import uniform, choice\n",
    "import os\n",
    "from azureml.train.automl import AutoMLConfig\n",
    "from azureml.data.dataset_factory import TabularDatasetFactory\n",
    "from azureml.core import Environment\n",
    "from azureml.core.model import InferenceConfig\n",
    "from azureml.core.model import Model\n",
    "from azureml.core.webservice import AciWebservice\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dataset\n",
    "\n",
    "Get data. In the cell below, write code to access the data you will be using in this project. Remember that the dataset needs to be external."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "gather": {
     "logged": 1598531917374
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [],
   "source": [
    "ws = Workspace.from_config()\n",
    "experiment_name = 'heartDiseaseHyperDrive'\n",
    "experiment=Experiment(ws, experiment_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found existing compute cluster\n",
      "{'currentNodeCount': 1, 'targetNodeCount': 1, 'nodeStateCounts': {'preparingNodeCount': 1, 'runningNodeCount': 0, 'idleNodeCount': 0, 'unusableNodeCount': 0, 'leavingNodeCount': 0, 'preemptedNodeCount': 0}, 'allocationState': 'Steady', 'allocationStateTransitionTime': '2021-01-10T10:54:51.204000+00:00', 'errors': None, 'creationTime': '2021-01-10T10:50:19.835696+00:00', 'modifiedTime': '2021-01-10T10:50:35.780465+00:00', 'provisioningState': 'Succeeded', 'provisioningStateTransitionTime': None, 'scaleSettings': {'minNodeCount': 0, 'maxNodeCount': 4, 'nodeIdleTimeBeforeScaleDown': 'PT120S'}, 'vmPriority': 'Dedicated', 'vmSize': 'STANDARD_D2_V2'}\n"
     ]
    }
   ],
   "source": [
    "#Compute CLuster\n",
    "compute_cluster_name = 'project'\n",
    "try:\n",
    "    compute_cluster = ComputeTarget(workspace=ws,name=compute_cluster_name)\n",
    "    print(\"Found existing compute cluster\")\n",
    "except ComputeTargetException:\n",
    "    print(\"Creating new Compute Cluster\")\n",
    "    compute_cluster_config = AmlCompute.provisioning_configuration(vm_size = 'Standard_D2_V2', max_nodes = 4)\n",
    "    compute_cluster = ComputeTarget.create(ws, compute_cluster_name, compute_cluster_config)\n",
    "    compute_cluster.wait_for_completion(show_output = True)\n",
    "print(compute_cluster.get_status().serialize())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "gather": {
     "logged": 1598531923519
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "source": [
    "## Hyperdrive Configuration\n",
    "\n",
    "Explain the model you are using and the reason for chosing the different hyperparameters, termination policy and config settings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "gather": {
     "logged": 1598544893076
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "'SKLearn' estimator is deprecated. Please use 'ScriptRunConfig' from 'azureml.core.script_run_config' with your own defined environment or the AzureML-Tutorial curated environment.\n"
     ]
    }
   ],
   "source": [
    "# Create an early termination policy. This is not required if you are using Bayesian sampling.\n",
    "early_termination_policy = BanditPolicy(evaluation_interval = 2 , slack_factor = 0.1)\n",
    "\n",
    "#Create the different params that you will be using during training\n",
    "param_sampling = RandomParameterSampling({\n",
    "    '--max_iter' : choice([100,200,300,400]),\n",
    "    '--C' : choice([0.001, 0.01, 0.1, 1, 10, 100, 1000])\n",
    "})\n",
    "\n",
    "# Create your estimator and hyperdrive config\n",
    "estimator = SKLearn(source_directory = './', entry_script = 'train.py', compute_target = compute_cluster)\n",
    "\n",
    "hyperdrive_run_config = HyperDriveConfig(\n",
    "    estimator = estimator,\n",
    "    hyperparameter_sampling = param_sampling,\n",
    "    primary_metric_name = 'Accuracy',\n",
    "    primary_metric_goal = PrimaryMetricGoal.MAXIMIZE,\n",
    "    policy = early_termination_policy,\n",
    "    max_total_runs = 20,\n",
    "    max_concurrent_runs = 4\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "gather": {
     "logged": 1598544897941
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:If 'script' has been provided here and a script file name has been specified in 'run_config', 'script' provided in ScriptRunConfig initialization will take precedence.\n"
     ]
    }
   ],
   "source": [
    "# Submit your experiment\n",
    "hyperdrive_run = experiment.submit(config = hyperdrive_run_config)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "gather": {
     "logged": 1598544898497
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "source": [
    "## Run Details\n",
    "\n",
    "OPTIONAL: Write about the different models trained and their performance. Why do you think some models did better than others?\n",
    "\n",
    " In the cell below, use the `RunDetails` widget to show the different experiments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "gather": {
     "logged": 1598546648408
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "384d34b4d764432bab5ff41cea5c9e3d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "_HyperDriveWidget(widget_settings={'childWidgetDisplay': 'popup', 'send_telemetry': False, 'log_level': 'INFO'…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/aml.mini.widget.v1": "{\"status\": \"Completed\", \"workbench_run_details_uri\": \"https://ml.azure.com/experiments/heartDiseaseHyperDrive/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6?wsid=/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourcegroups/aml-quickstarts-134203/workspaces/quick-starts-ws-134203\", \"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"run_properties\": {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"created_utc\": \"2021-01-10T10:55:36.539139Z\", \"properties\": {\"primary_metric_config\": \"{\\\"name\\\": \\\"Accuracy\\\", \\\"goal\\\": \\\"maximize\\\"}\", \"resume_from\": \"null\", \"runTemplate\": \"HyperDrive\", \"azureml.runsource\": \"hyperdrive\", \"platform\": \"AML\", \"ContentSnapshotId\": \"061f20b6-7fd0-46f3-8af5-b1f158a60556\", \"score\": \"0.8888888888888888\", \"best_child_run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\", \"best_metric_status\": \"Succeeded\"}, \"tags\": {\"_aml_system_max_concurrent_jobs\": \"4\", \"max_concurrent_jobs\": \"4\", \"_aml_system_max_total_jobs\": \"20\", \"max_total_jobs\": \"20\", \"_aml_system_max_duration_minutes\": \"10080\", \"max_duration_minutes\": \"10080\", \"_aml_system_policy_config\": \"{\\\"name\\\": \\\"BANDIT\\\", \\\"properties\\\": {\\\"evaluation_interval\\\": 2, \\\"delay_evaluation\\\": 0, \\\"slack_factor\\\": 0.1}}\", \"policy_config\": \"{\\\"name\\\": \\\"BANDIT\\\", \\\"properties\\\": {\\\"evaluation_interval\\\": 2, \\\"delay_evaluation\\\": 0, \\\"slack_factor\\\": 0.1}}\", \"_aml_system_generator_config\": \"{\\\"name\\\": \\\"RANDOM\\\", \\\"parameter_space\\\": {\\\"--max_iter\\\": [\\\"choice\\\", [[100, 200, 300, 400]]], \\\"--C\\\": [\\\"choice\\\", [[0.001, 0.01, 0.1, 1, 10, 100, 1000]]]}}\", \"generator_config\": \"{\\\"name\\\": \\\"RANDOM\\\", \\\"parameter_space\\\": {\\\"--max_iter\\\": [\\\"choice\\\", [[100, 200, 300, 400]]], \\\"--C\\\": [\\\"choice\\\", [[0.001, 0.01, 0.1, 1, 10, 100, 1000]]]}}\", \"_aml_system_primary_metric_config\": \"{\\\"name\\\": \\\"Accuracy\\\", \\\"goal\\\": \\\"maximize\\\"}\", \"primary_metric_config\": \"{\\\"name\\\": \\\"Accuracy\\\", \\\"goal\\\": \\\"maximize\\\"}\", \"_aml_system_platform_config\": \"{\\\"ServiceAddress\\\": \\\"https://southcentralus.experiments.azureml.net\\\", \\\"ServiceArmScope\\\": \\\"subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/heartDiseaseHyperDrive\\\", \\\"SubscriptionId\\\": \\\"9e65f93e-bdd8-437b-b1e8-0647cd6098f7\\\", \\\"ResourceGroupName\\\": \\\"aml-quickstarts-134203\\\", \\\"WorkspaceName\\\": \\\"quick-starts-ws-134203\\\", \\\"ExperimentName\\\": \\\"heartDiseaseHyperDrive\\\", \\\"Definition\\\": {\\\"Overrides\\\": {\\\"script\\\": \\\"train.py\\\", \\\"arguments\\\": [], \\\"target\\\": \\\"project\\\", \\\"framework\\\": \\\"Python\\\", \\\"communicator\\\": \\\"None\\\", \\\"maxRunDurationSeconds\\\": null, \\\"nodeCount\\\": 1, \\\"environment\\\": {\\\"name\\\": null, \\\"version\\\": null, \\\"environmentVariables\\\": {\\\"EXAMPLE_ENV_VAR\\\": \\\"EXAMPLE_VALUE\\\"}, \\\"python\\\": {\\\"userManagedDependencies\\\": true, \\\"interpreterPath\\\": \\\"python\\\", \\\"condaDependenciesFile\\\": null, \\\"baseCondaEnvironment\\\": null, \\\"condaDependencies\\\": {\\\"name\\\": \\\"project_environment\\\", \\\"dependencies\\\": [\\\"python=3.6.2\\\", {\\\"pip\\\": [\\\"azureml-defaults\\\"]}], \\\"channels\\\": [\\\"anaconda\\\", \\\"conda-forge\\\"]}}, \\\"docker\\\": {\\\"enabled\\\": true, \\\"baseImage\\\": \\\"sklearn:0.20.3-cpu\\\", \\\"baseDockerfile\\\": null, \\\"sharedVolumes\\\": true, \\\"shmSize\\\": \\\"2g\\\", \\\"arguments\\\": [], \\\"baseImageRegistry\\\": {\\\"address\\\": \\\"viennaprivate.azurecr.io\\\", \\\"username\\\": null, \\\"password\\\": null, \\\"registryIdentity\\\": null}, \\\"platform\\\": {\\\"os\\\": \\\"Linux\\\", \\\"architecture\\\": \\\"amd64\\\"}}, \\\"spark\\\": {\\\"repositories\\\": [], \\\"packages\\\": [], \\\"precachePackages\\\": false}, \\\"databricks\\\": {\\\"mavenLibraries\\\": [], \\\"pypiLibraries\\\": [], \\\"rcranLibraries\\\": [], \\\"jarLibraries\\\": [], \\\"eggLibraries\\\": []}, \\\"r\\\": null, \\\"inferencingStackVersion\\\": null}, \\\"history\\\": {\\\"outputCollection\\\": true, \\\"snapshotProject\\\": true, \\\"directoriesToWatch\\\": [\\\"logs\\\"]}, \\\"spark\\\": {\\\"configuration\\\": {\\\"spark.app.name\\\": \\\"Azure ML Experiment\\\", \\\"spark.yarn.maxAppAttempts\\\": 1}}, \\\"hdi\\\": {\\\"yarnDeployMode\\\": \\\"cluster\\\"}, \\\"tensorflow\\\": {\\\"workerCount\\\": 1, \\\"parameterServerCount\\\": 1}, \\\"mpi\\\": {\\\"processCountPerNode\\\": 1, \\\"nodeCount\\\": 1}, \\\"paralleltask\\\": {\\\"maxRetriesPerWorker\\\": 0, \\\"workerCountPerNode\\\": 1, \\\"terminalExitCodes\\\": null}, \\\"dataReferences\\\": {}, \\\"data\\\": {}, \\\"outputData\\\": {}, \\\"sourceDirectoryDataStore\\\": null, \\\"amlcompute\\\": {\\\"vmSize\\\": null, \\\"vmPriority\\\": null, \\\"retainCluster\\\": false, \\\"name\\\": null, \\\"clusterMaxNodeCount\\\": 1}, \\\"command\\\": \\\"\\\"}, \\\"TargetDetails\\\": null, \\\"SnapshotId\\\": \\\"061f20b6-7fd0-46f3-8af5-b1f158a60556\\\", \\\"TelemetryValues\\\": {\\\"amlClientType\\\": \\\"azureml-sdk-train\\\", \\\"amlClientModule\\\": \\\"[Scrubbed]\\\", \\\"amlClientFunction\\\": \\\"[Scrubbed]\\\", \\\"tenantId\\\": \\\"660b3398-b80e-49d2-bc5b-ac1dc93b5254\\\", \\\"amlClientRequestId\\\": \\\"33097045-dece-4582-b9b9-7198b51e63e2\\\", \\\"amlClientSessionId\\\": \\\"4d139e2b-6e20-4988-92e5-6008d0983dc4\\\", \\\"subscriptionId\\\": \\\"9e65f93e-bdd8-437b-b1e8-0647cd6098f7\\\", \\\"estimator\\\": \\\"SKLearn\\\", \\\"samplingMethod\\\": \\\"RANDOM\\\", \\\"terminationPolicy\\\": \\\"Bandit\\\", \\\"primaryMetricGoal\\\": \\\"maximize\\\", \\\"maxTotalRuns\\\": 20, \\\"maxConcurrentRuns\\\": 4, \\\"maxDurationMinutes\\\": 10080, \\\"vmSize\\\": null}}}\", \"platform_config\": \"{\\\"ServiceAddress\\\": \\\"https://southcentralus.experiments.azureml.net\\\", \\\"ServiceArmScope\\\": \\\"subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/heartDiseaseHyperDrive\\\", \\\"SubscriptionId\\\": \\\"9e65f93e-bdd8-437b-b1e8-0647cd6098f7\\\", \\\"ResourceGroupName\\\": \\\"aml-quickstarts-134203\\\", \\\"WorkspaceName\\\": \\\"quick-starts-ws-134203\\\", \\\"ExperimentName\\\": \\\"heartDiseaseHyperDrive\\\", \\\"Definition\\\": {\\\"Overrides\\\": {\\\"script\\\": \\\"train.py\\\", \\\"arguments\\\": [], \\\"target\\\": \\\"project\\\", \\\"framework\\\": \\\"Python\\\", \\\"communicator\\\": \\\"None\\\", \\\"maxRunDurationSeconds\\\": null, \\\"nodeCount\\\": 1, \\\"environment\\\": {\\\"name\\\": null, \\\"version\\\": null, \\\"environmentVariables\\\": {\\\"EXAMPLE_ENV_VAR\\\": \\\"EXAMPLE_VALUE\\\"}, \\\"python\\\": {\\\"userManagedDependencies\\\": true, \\\"interpreterPath\\\": \\\"python\\\", \\\"condaDependenciesFile\\\": null, \\\"baseCondaEnvironment\\\": null, \\\"condaDependencies\\\": {\\\"name\\\": \\\"project_environment\\\", \\\"dependencies\\\": [\\\"python=3.6.2\\\", {\\\"pip\\\": [\\\"azureml-defaults\\\"]}], \\\"channels\\\": [\\\"anaconda\\\", \\\"conda-forge\\\"]}}, \\\"docker\\\": {\\\"enabled\\\": true, \\\"baseImage\\\": \\\"sklearn:0.20.3-cpu\\\", \\\"baseDockerfile\\\": null, \\\"sharedVolumes\\\": true, \\\"shmSize\\\": \\\"2g\\\", \\\"arguments\\\": [], \\\"baseImageRegistry\\\": {\\\"address\\\": \\\"viennaprivate.azurecr.io\\\", \\\"username\\\": null, \\\"password\\\": null, \\\"registryIdentity\\\": null}, \\\"platform\\\": {\\\"os\\\": \\\"Linux\\\", \\\"architecture\\\": \\\"amd64\\\"}}, \\\"spark\\\": {\\\"repositories\\\": [], \\\"packages\\\": [], \\\"precachePackages\\\": false}, \\\"databricks\\\": {\\\"mavenLibraries\\\": [], \\\"pypiLibraries\\\": [], \\\"rcranLibraries\\\": [], \\\"jarLibraries\\\": [], \\\"eggLibraries\\\": []}, \\\"r\\\": null, \\\"inferencingStackVersion\\\": null}, \\\"history\\\": {\\\"outputCollection\\\": true, \\\"snapshotProject\\\": true, \\\"directoriesToWatch\\\": [\\\"logs\\\"]}, \\\"spark\\\": {\\\"configuration\\\": {\\\"spark.app.name\\\": \\\"Azure ML Experiment\\\", \\\"spark.yarn.maxAppAttempts\\\": 1}}, \\\"hdi\\\": {\\\"yarnDeployMode\\\": \\\"cluster\\\"}, \\\"tensorflow\\\": {\\\"workerCount\\\": 1, \\\"parameterServerCount\\\": 1}, \\\"mpi\\\": {\\\"processCountPerNode\\\": 1, \\\"nodeCount\\\": 1}, \\\"paralleltask\\\": {\\\"maxRetriesPerWorker\\\": 0, \\\"workerCountPerNode\\\": 1, \\\"terminalExitCodes\\\": null}, \\\"dataReferences\\\": {}, \\\"data\\\": {}, \\\"outputData\\\": {}, \\\"sourceDirectoryDataStore\\\": null, \\\"amlcompute\\\": {\\\"vmSize\\\": null, \\\"vmPriority\\\": null, \\\"retainCluster\\\": false, \\\"name\\\": null, \\\"clusterMaxNodeCount\\\": 1}, \\\"command\\\": \\\"\\\"}, \\\"TargetDetails\\\": null, \\\"SnapshotId\\\": \\\"061f20b6-7fd0-46f3-8af5-b1f158a60556\\\", \\\"TelemetryValues\\\": {\\\"amlClientType\\\": \\\"azureml-sdk-train\\\", \\\"amlClientModule\\\": \\\"[Scrubbed]\\\", \\\"amlClientFunction\\\": \\\"[Scrubbed]\\\", \\\"tenantId\\\": \\\"660b3398-b80e-49d2-bc5b-ac1dc93b5254\\\", \\\"amlClientRequestId\\\": \\\"33097045-dece-4582-b9b9-7198b51e63e2\\\", \\\"amlClientSessionId\\\": \\\"4d139e2b-6e20-4988-92e5-6008d0983dc4\\\", \\\"subscriptionId\\\": \\\"9e65f93e-bdd8-437b-b1e8-0647cd6098f7\\\", \\\"estimator\\\": \\\"SKLearn\\\", \\\"samplingMethod\\\": \\\"RANDOM\\\", \\\"terminationPolicy\\\": \\\"Bandit\\\", \\\"primaryMetricGoal\\\": \\\"maximize\\\", \\\"maxTotalRuns\\\": 20, \\\"maxConcurrentRuns\\\": 4, \\\"maxDurationMinutes\\\": 10080, \\\"vmSize\\\": null}}}\", \"_aml_system_resume_child_runs\": \"null\", \"resume_child_runs\": \"null\", \"_aml_system_all_jobs_generated\": \"true\", \"all_jobs_generated\": \"true\", \"_aml_system_cancellation_requested\": \"false\", \"cancellation_requested\": \"false\", \"_aml_system_progress_metadata_evaluation_timestamp\": \"\\\"2021-01-10T10:55:37.551657\\\"\", \"progress_metadata_evaluation_timestamp\": \"\\\"2021-01-10T10:55:37.551657\\\"\", \"_aml_system_progress_metadata_digest\": \"\\\"1ee052aa02615618c756a70edd419e8a0c0058f8a3a654c3cc182a7ccdcfadc3\\\"\", \"progress_metadata_digest\": \"\\\"1ee052aa02615618c756a70edd419e8a0c0058f8a3a654c3cc182a7ccdcfadc3\\\"\", \"_aml_system_progress_metadata_active_timestamp\": \"\\\"2021-01-10T10:55:37.551657\\\"\", \"progress_metadata_active_timestamp\": \"\\\"2021-01-10T10:55:37.551657\\\"\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 200}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1\": \"{\\\"--C\\\": 0.1, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1\": \"{\\\"--C\\\": 0.1, \\\"--max_iter\\\": 200}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 200}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 400}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 400}\", \"_aml_system_environment_preparation_status\": \"PREPARED\", \"environment_preparation_status\": \"PREPARED\", \"_aml_system_prepare_run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_preparation\", \"prepare_run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_preparation\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 100}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 100}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 200}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 400}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 400}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8\": \"{\\\"--C\\\": 0.001, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8\": \"{\\\"--C\\\": 0.001, \\\"--max_iter\\\": 200}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9\": \"{\\\"--C\\\": 0.1, \\\"--max_iter\\\": 100}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9\": \"{\\\"--C\\\": 0.1, \\\"--max_iter\\\": 100}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10\": \"{\\\"--C\\\": 1000, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10\": \"{\\\"--C\\\": 1000, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 100}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12\": \"{\\\"--C\\\": 10, \\\"--max_iter\\\": 100}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14\": \"{\\\"--C\\\": 0.001, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14\": \"{\\\"--C\\\": 0.001, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 300}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 300}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 400}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16\": \"{\\\"--C\\\": 1, \\\"--max_iter\\\": 400}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 100}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 100}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 400}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18\": \"{\\\"--C\\\": 0.01, \\\"--max_iter\\\": 400}\", \"_aml_system_HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 200}\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19\": \"{\\\"--C\\\": 100, \\\"--max_iter\\\": 200}\", \"_aml_system_final_best_metric_update_retry_count\": \"2\", \"final_best_metric_update_retry_count\": \"2\"}, \"end_time_utc\": \"2021-01-10T11:08:16.729028Z\", \"status\": \"Completed\", \"log_files\": {\"azureml-logs/hyperdrive.txt\": \"https://mlstrg134203.blob.core.windows.net/azureml/ExperimentRun/dcid.HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6/azureml-logs/hyperdrive.txt?sv=2019-02-02&sr=b&sig=6p3jg2eUauDFj5HDWmrCdbOnyVb9WttlIgLUsJFtLC8%3D&st=2021-01-10T11%3A59%3A38Z&se=2021-01-10T20%3A09%3A38Z&sp=r\"}, \"log_groups\": [[\"azureml-logs/hyperdrive.txt\"]], \"run_duration\": \"0:12:40\", \"hyper_parameters\": {\"--max_iter\": [\"choice\", [[100, 200, 300, 400]]], \"--C\": [\"choice\", [[0.001, 0.01, 0.1, 1, 10, 100, 1000]]]}}, \"child_runs\": [{\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1\", \"run_number\": 3, \"metric\": 0.86666667, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T10:58:34.845605Z\", \"end_time\": \"2021-01-10T11:00:42.943447Z\", \"created_time\": \"2021-01-10T10:56:09.483526Z\", \"created_time_dt\": \"2021-01-10T10:56:09.483526Z\", \"duration\": \"0:04:33\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.1, \"param_--max_iter\": 200, \"best_metric\": 0.86666667}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0\", \"run_number\": 4, \"metric\": 0.84444444, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T10:58:32.883572Z\", \"end_time\": \"2021-01-10T11:00:51.224087Z\", \"created_time\": \"2021-01-10T10:56:09.608977Z\", \"created_time_dt\": \"2021-01-10T10:56:09.608977Z\", \"duration\": \"0:04:41\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.01, \"param_--max_iter\": 200, \"best_metric\": 0.86666667}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2\", \"run_number\": 5, \"metric\": 0.87777778, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T10:58:35.174332Z\", \"end_time\": \"2021-01-10T11:00:37.912608Z\", \"created_time\": \"2021-01-10T10:56:09.780038Z\", \"created_time_dt\": \"2021-01-10T10:56:09.780038Z\", \"duration\": \"0:04:28\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 1, \"param_--max_iter\": 200, \"best_metric\": 0.87777778}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\", \"run_number\": 6, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T10:58:57.599118Z\", \"end_time\": \"2021-01-10T11:00:57.479272Z\", \"created_time\": \"2021-01-10T10:56:10.108365Z\", \"created_time_dt\": \"2021-01-10T10:56:10.108365Z\", \"duration\": \"0:04:47\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 100, \"param_--max_iter\": 400, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4\", \"run_number\": 7, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:00:57.975566Z\", \"end_time\": \"2021-01-10T11:01:38.11573Z\", \"created_time\": \"2021-01-10T11:00:46.697948Z\", \"created_time_dt\": \"2021-01-10T11:00:46.697948Z\", \"duration\": \"0:00:51\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 100, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5\", \"run_number\": 8, \"metric\": 0.87777778, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:01:28.759974Z\", \"end_time\": \"2021-01-10T11:02:17.278173Z\", \"created_time\": \"2021-01-10T11:01:18.584519Z\", \"created_time_dt\": \"2021-01-10T11:01:18.584519Z\", \"duration\": \"0:00:58\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 1, \"param_--max_iter\": 100, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6\", \"run_number\": 9, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:01:28.908243Z\", \"end_time\": \"2021-01-10T11:02:15.131902Z\", \"created_time\": \"2021-01-10T11:01:18.676994Z\", \"created_time_dt\": \"2021-01-10T11:01:18.676994Z\", \"duration\": \"0:00:56\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 10, \"param_--max_iter\": 200, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7\", \"run_number\": 10, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:01:41.52846Z\", \"end_time\": \"2021-01-10T11:02:30.953104Z\", \"created_time\": \"2021-01-10T11:01:20.104946Z\", \"created_time_dt\": \"2021-01-10T11:01:20.104946Z\", \"duration\": \"0:01:10\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 10, \"param_--max_iter\": 400, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8\", \"run_number\": 11, \"metric\": 0.75555556, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:02:19.887103Z\", \"end_time\": \"2021-01-10T11:03:08.188722Z\", \"created_time\": \"2021-01-10T11:01:51.444696Z\", \"created_time_dt\": \"2021-01-10T11:01:51.444696Z\", \"duration\": \"0:01:16\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.001, \"param_--max_iter\": 200, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11\", \"run_number\": 12, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:03:02.722543Z\", \"end_time\": \"2021-01-10T11:03:53.026492Z\", \"created_time\": \"2021-01-10T11:02:53.933505Z\", \"created_time_dt\": \"2021-01-10T11:02:53.933505Z\", \"duration\": \"0:00:59\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 10, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9\", \"run_number\": 13, \"metric\": 0.86666667, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:03:03.226028Z\", \"end_time\": \"2021-01-10T11:03:47.833483Z\", \"created_time\": \"2021-01-10T11:02:54.498506Z\", \"created_time_dt\": \"2021-01-10T11:02:54.498506Z\", \"duration\": \"0:00:53\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.1, \"param_--max_iter\": 100, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10\", \"run_number\": 14, \"metric\": 0.87777778, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:03:09.968292Z\", \"end_time\": \"2021-01-10T11:03:53.744509Z\", \"created_time\": \"2021-01-10T11:02:54.700298Z\", \"created_time_dt\": \"2021-01-10T11:02:54.700298Z\", \"duration\": \"0:00:59\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 1000, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12\", \"run_number\": 15, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:03:49.192113Z\", \"end_time\": \"2021-01-10T11:04:33.191442Z\", \"created_time\": \"2021-01-10T11:03:26.299364Z\", \"created_time_dt\": \"2021-01-10T11:03:26.299364Z\", \"duration\": \"0:01:06\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 10, \"param_--max_iter\": 100, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13\", \"run_number\": 16, \"metric\": 0.87777778, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:04:39.774489Z\", \"end_time\": \"2021-01-10T11:05:20.128972Z\", \"created_time\": \"2021-01-10T11:04:29.416714Z\", \"created_time_dt\": \"2021-01-10T11:04:29.416714Z\", \"duration\": \"0:00:50\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 1, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14\", \"run_number\": 17, \"metric\": 0.75555556, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:04:38.370298Z\", \"end_time\": \"2021-01-10T11:05:17.313768Z\", \"created_time\": \"2021-01-10T11:04:29.588501Z\", \"created_time_dt\": \"2021-01-10T11:04:29.588501Z\", \"duration\": \"0:00:47\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.001, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15\", \"run_number\": 18, \"metric\": 0.84444444, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:04:41.176136Z\", \"end_time\": \"2021-01-10T11:05:22.070988Z\", \"created_time\": \"2021-01-10T11:04:29.970955Z\", \"created_time_dt\": \"2021-01-10T11:04:29.970955Z\", \"duration\": \"0:00:52\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.01, \"param_--max_iter\": 300, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16\", \"run_number\": 19, \"metric\": 0.87777778, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:05:14.008785Z\", \"end_time\": \"2021-01-10T11:05:54.585602Z\", \"created_time\": \"2021-01-10T11:05:02.016976Z\", \"created_time_dt\": \"2021-01-10T11:05:02.016976Z\", \"duration\": \"0:00:52\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 1, \"param_--max_iter\": 400, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18\", \"run_number\": 20, \"metric\": 0.84444444, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:05:44.650906Z\", \"end_time\": \"2021-01-10T11:06:28.361133Z\", \"created_time\": \"2021-01-10T11:05:34.405385Z\", \"created_time_dt\": \"2021-01-10T11:05:34.405385Z\", \"duration\": \"0:00:53\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 0.01, \"param_--max_iter\": 400, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17\", \"run_number\": 21, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:05:43.761815Z\", \"end_time\": \"2021-01-10T11:06:22.796455Z\", \"created_time\": \"2021-01-10T11:05:34.540549Z\", \"created_time_dt\": \"2021-01-10T11:05:34.540549Z\", \"duration\": \"0:00:48\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 100, \"param_--max_iter\": 100, \"best_metric\": 0.88888889}, {\"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19\", \"run_number\": 22, \"metric\": 0.88888889, \"status\": \"Completed\", \"run_type\": \"azureml.scriptrun\", \"training_percent\": null, \"start_time\": \"2021-01-10T11:06:18.198888Z\", \"end_time\": \"2021-01-10T11:07:02.761535Z\", \"created_time\": \"2021-01-10T11:06:08.205719Z\", \"created_time_dt\": \"2021-01-10T11:06:08.205719Z\", \"duration\": \"0:00:54\", \"hyperdrive_id\": \"7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"arguments\": null, \"param_--C\": 100, \"param_--max_iter\": 200, \"best_metric\": 0.88888889}], \"children_metrics\": {\"categories\": [0], \"series\": {\"Regularization Strength:\": [{\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"markers\", \"name\": \"Regularization Strength:\", \"stepped\": false, \"type\": \"scatter\", \"data\": [0.1, 0.01, 1.0, 100.0, 100.0, 1.0, 10.0, 10.0, 0.001, 10.0, 0.1, 1000.0, 10.0, 1.0, 0.001, 0.01, 1.0, 0.01, 100.0, 100.0]}, {\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"lines\", \"name\": \"Regularization Strength:_max\", \"stepped\": true, \"type\": \"scatter\", \"data\": [0.1, 0.1, 1.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 100.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0, 1000.0]}], \"Max iterations:\": [{\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"markers\", \"name\": \"Max iterations:\", \"stepped\": false, \"type\": \"scatter\", \"data\": [200, 200, 200, 400, 300, 100, 200, 400, 200, 300, 100, 300, 100, 300, 300, 300, 400, 400, 100, 200]}, {\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"lines\", \"name\": \"Max iterations:_max\", \"stepped\": true, \"type\": \"scatter\", \"data\": [200, 200, 200, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400, 400]}], \"Accuracy\": [{\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"markers\", \"name\": \"Accuracy\", \"stepped\": false, \"type\": \"scatter\", \"data\": [0.8666666666666667, 0.8444444444444444, 0.8777777777777778, 0.8888888888888888, 0.8888888888888888, 0.8777777777777778, 0.8888888888888888, 0.8888888888888888, 0.7555555555555555, 0.8888888888888888, 0.8666666666666667, 0.8777777777777778, 0.8888888888888888, 0.8777777777777778, 0.7555555555555555, 0.8444444444444444, 0.8777777777777778, 0.8444444444444444, 0.8888888888888888, 0.8888888888888888]}, {\"categories\": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22], \"mode\": \"lines\", \"name\": \"Accuracy_max\", \"stepped\": true, \"type\": \"scatter\", \"data\": [0.8666666666666667, 0.8666666666666667, 0.8777777777777778, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888, 0.8888888888888888]}]}, \"metricName\": null, \"primaryMetricName\": \"Accuracy\", \"showLegend\": false}, \"run_metrics\": [{\"name\": \"best_child_by_primary_metric\", \"run_id\": \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6\", \"categories\": [0], \"series\": [{\"data\": [{\"metric_name\": [\"Accuracy\", \"Accuracy\"], \"timestamp\": [\"2021-01-10 11:01:17.159025+00:00\", \"2021-01-10 11:01:17.159025+00:00\"], \"run_id\": [\"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\", \"HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3\"], \"metric_value\": [0.8888888888888888, 0.8888888888888888], \"final\": [false, true]}]}]}], \"run_logs\": \"[2021-01-10T10:55:37.005857][API][INFO]Experiment created\\r\\n[2021-01-10T10:55:37.868877][GENERATOR][INFO]Trying to sample '4' jobs from the hyperparameter space\\r\\n[2021-01-10T10:55:38.1359581Z][SCHEDULER][INFO]The execution environment is being prepared. Please be patient as it can take a few minutes.\\r\\n[2021-01-10T10:55:38.192262][GENERATOR][INFO]Successfully sampled '4' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T10:56:08.8656772Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0'\\r\\n[2021-01-10T10:56:08.8671376Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1'\\r\\n[2021-01-10T10:56:08.8649447Z][SCHEDULER][INFO]The execution environment was successfully prepared.\\r\\n[2021-01-10T10:56:08.8681707Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2'\\r\\n[2021-01-10T10:56:08.9231223Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3'\\r\\n[2021-01-10T10:56:09.6512166Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1'\\r\\n[2021-01-10T10:56:09.7227256Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0'\\r\\n[2021-01-10T10:56:09.9495572Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2'\\r\\n[2021-01-10T10:56:11.2526466Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3'\\r\\n[2021-01-10T10:58:38.038069][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T10:59:08.035521][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T10:59:38.181959][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:00:09.231119][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_2, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:00:38.756886][GENERATOR][INFO]Trying to sample '1' jobs from the hyperparameter space\\r\\n[2021-01-10T11:00:38.897146][GENERATOR][INFO]Successfully sampled '1' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:00:39.697686][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_0, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_1, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_3] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:00:45.8846265Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4'\\r\\n[2021-01-10T11:00:46.9132179Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4'\\r\\n[2021-01-10T11:01:09.552519][GENERATOR][INFO]Successfully sampled '3' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:01:17.5173416Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5'\\r\\n[2021-01-10T11:01:17.5406204Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7'\\r\\n[2021-01-10T11:01:17.5192049Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6'\\r\\n[2021-01-10T11:01:18.8557131Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5'\\r\\n[2021-01-10T11:01:18.8892869Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6'\\r\\n[2021-01-10T11:01:09.398773][GENERATOR][INFO]Trying to sample '3' jobs from the hyperparameter space\\r\\n[2021-01-10T11:01:12.694073][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_4] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:01:20.2961794Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7'\\r\\n[2021-01-10T11:01:40.311624][GENERATOR][INFO]Trying to sample '1' jobs from the hyperparameter space\\r\\n[2021-01-10T11:01:40.487654][GENERATOR][INFO]Successfully sampled '1' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:01:42.881618][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:01:50.7599557Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8'\\r\\n[2021-01-10T11:01:51.6754103Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8'\\r\\n[2021-01-10T11:02:13.187984][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_5, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_6, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_7] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:02:42.479766][GENERATOR][INFO]Trying to sample '3' jobs from the hyperparameter space\\r\\n[2021-01-10T11:02:42.799203][GENERATOR][INFO]Successfully sampled '3' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:02:44.440010][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_8] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:02:53.2161158Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10'\\r\\n[2021-01-10T11:02:53.1963497Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11'\\r\\n[2021-01-10T11:02:54.0844893Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11'\\r\\n[2021-01-10T11:02:54.6527620Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9'\\r\\n[2021-01-10T11:02:54.8718599Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10'\\r\\n[2021-01-10T11:02:53.2314199Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9'\\r\\n[2021-01-10T11:03:13.288690][GENERATOR][INFO]Trying to sample '1' jobs from the hyperparameter space\\r\\n[2021-01-10T11:03:13.591271][GENERATOR][INFO]Successfully sampled '1' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:03:15.378211][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_9, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_11] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:03:25.5100731Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12'\\r\\n[2021-01-10T11:03:26.5193298Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12'\\r\\n[2021-01-10T11:03:46.493584][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_10] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:04:17.332841][GENERATOR][INFO]Trying to sample '3' jobs from the hyperparameter space\\r\\n[2021-01-10T11:04:17.447312][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_12] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:04:17.666563][GENERATOR][INFO]Successfully sampled '3' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:04:28.5863669Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13'\\r\\n[2021-01-10T11:04:28.5849664Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15'\\r\\n[2021-01-10T11:04:28.5856877Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14'\\r\\n[2021-01-10T11:04:29.6754050Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13'\\r\\n[2021-01-10T11:04:29.7081916Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14'\\r\\n[2021-01-10T11:04:30.1891578Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15'\\r\\n[2021-01-10T11:04:48.642787][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_13, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_14, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:04:50.261093][GENERATOR][INFO]Trying to sample '1' jobs from the hyperparameter space\\r\\n[2021-01-10T11:04:50.397646][GENERATOR][INFO]Successfully sampled '1' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:05:00.8764956Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16'\\r\\n[2021-01-10T11:05:02.4641577Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16'\\r\\n[2021-01-10T11:05:19.611530][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_15, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_16] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:05:21.545497][GENERATOR][INFO]Trying to sample '2' jobs from the hyperparameter space\\r\\n[2021-01-10T11:05:21.850178][GENERATOR][INFO]Successfully sampled '2' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:05:33.4066115Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17'\\r\\n[2021-01-10T11:05:33.4078567Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18'\\r\\n[2021-01-10T11:05:34.6571045Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17'\\r\\n[2021-01-10T11:05:34.6328205Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18'\\r\\n[2021-01-10T11:05:50.185287][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_17, https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_18] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:05:52.627276][GENERATOR][INFO]Trying to sample '1' jobs from the hyperparameter space\\r\\n[2021-01-10T11:05:52.928548][GENERATOR][INFO]Successfully sampled '1' jobs, they will soon be submitted to the execution target.\\r\\n[2021-01-10T11:06:05.9904303Z][SCHEDULER][INFO]Scheduling job, id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19'\\r\\n[2021-01-10T11:06:08.3178922Z][SCHEDULER][INFO]Successfully scheduled a job. Id='HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19'\\r\\n[2021-01-10T11:06:23.571361][GENERATOR][INFO]Max number of jobs '20' reached for experiment.\\r\\n[2021-01-10T11:06:24.005662][GENERATOR][INFO]All jobs generated.\\r\\n[2021-01-10T11:06:24.611319][ENFORCER][INFO]Jobs [https://southcentralus.experiments.azureml.net/subscriptions/9e65f93e-bdd8-437b-b1e8-0647cd6098f7/resourceGroups/aml-quickstarts-134203/providers/Microsoft.MachineLearningServices/workspaces/quick-starts-ws-134203/experiments/**SCRUBBED**/runs/HD_7649cc2e-65e4-4ec1-89ec-7dca0440f5d6_19] do not contain any metrics with the primary metric name at this moment, policy cannot be applied.\\r\\n[2021-01-10T11:08:17.230567][CONTROLLER][INFO]Experiment was 'ExperimentStatus.RUNNING', is 'ExperimentStatus.FINISHED'.\\n\\nRun is completed.\", \"graph\": {}, \"widget_settings\": {\"childWidgetDisplay\": \"popup\", \"send_telemetry\": false, \"log_level\": \"INFO\", \"sdk_version\": \"1.19.0\"}, \"loading\": false}"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RunDetails(hyperdrive_run).show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Best Model\n",
    "\n",
    "In the cell below, get the best model from the hyperdrive experiments and display all the properties of the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "gather": {
     "logged": 1598546650307
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['--C', '100', '--max_iter', '400']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['azureml-logs/55_azureml-execution-tvmps_c92231fbec862850c5704cc8e8183627f7cd1abd155a576554ddddf2911c7893_d.txt',\n",
       " 'azureml-logs/65_job_prep-tvmps_c92231fbec862850c5704cc8e8183627f7cd1abd155a576554ddddf2911c7893_d.txt',\n",
       " 'azureml-logs/70_driver_log.txt',\n",
       " 'azureml-logs/75_job_post-tvmps_c92231fbec862850c5704cc8e8183627f7cd1abd155a576554ddddf2911c7893_d.txt',\n",
       " 'azureml-logs/process_info.json',\n",
       " 'azureml-logs/process_status.json',\n",
       " 'logs/azureml/100_azureml.log',\n",
       " 'logs/azureml/job_prep_azureml.log',\n",
       " 'logs/azureml/job_release_azureml.log',\n",
       " 'outputs/LogisticRegression.pkl']"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hyperdrive_best_run = hyperdrive_run.get_best_run_by_primary_metric()\n",
    "print(hyperdrive_best_run.get_details()['runDefinition']['arguments'])\n",
    "hyperdrive_best_run.get_file_names()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Regularization Strength: 100.0\n",
      "Max iterations: 400\n",
      "Accuracy 0.8888888888888888\n"
     ]
    }
   ],
   "source": [
    "hyperdrive_best_run_metrics = hyperdrive_best_run.get_metrics()\n",
    "for metric_name in hyperdrive_best_run_metrics:\n",
    "    metric = hyperdrive_best_run_metrics[metric_name]\n",
    "    print(metric_name, metric)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "gather": {
     "logged": 1598546657829
    },
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "outputs": [],
   "source": [
    "# Save the best model\n",
    "model=hyperdrive_best_run.register_model(model_name='hyperdrivebestrun', model_path='outputs/LogisticRegression.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": false,
     "source_hidden": false
    },
    "nteract": {
     "transient": {
      "deleting": false
     }
    }
   },
   "source": [
    "## Model Deployment\n",
    "\n",
    "Remember you have to deploy only one of the two models you trained.. Perform the steps in the rest of this notebook only if you wish to deploy this model.\n",
    "\n",
    " In the cell below, register the model, create an inference config and deploy the model as a web service."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "myenv=Environment.from_conda_specification(name='myenv',file_path='conda_env.yml')\n",
    "inference_config = InferenceConfig(entry_script='score.py',environment=myenv)\n",
    "aci_config = AciWebservice.deploy_configuration(cpu_cores = 1, memory_gb = 1, auth_enabled = True)\n",
    "service= Model.deploy(workspace=ws,\n",
    "                     name='heart-disease',\n",
    "                     models=[model],\n",
    "                     inference_config=inference_config,\n",
    "                     deployment_config=aci_config,\n",
    "                     overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tips: You can try get_logs(): https://aka.ms/debugimage#dockerlog or local deployment: https://aka.ms/debugimage#debug-locally to debug if deployment takes longer than 10 minutes.\n",
      "Running....\n",
      "Succeeded\n",
      "ACI service creation operation finished, operation \"Succeeded\"\n"
     ]
    }
   ],
   "source": [
    "service.wait_for_deployment(show_output=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Standout Suggestions - Application Insights\n",
    "service.update(enable_app_insights=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " In the cell below, send a request to the web service you deployed to test it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = TabularDatasetFactory.from_delimited_files(\"https://raw.githubusercontent.com/GowthamiWudaru/heart-Disease-Prediction-With-Azure/main/heartDisease.csv\")\n",
    "df=ds.to_pandas_dataframe().drop(['num'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\"result\": [0, 1, 1]}\n"
     ]
    }
   ],
   "source": [
    "input_payload = json.dumps({\n",
    "    'data': df.sample(3).to_dict()\n",
    "})\n",
    "output = service.run(input_payload)\n",
    "print(output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " In the cell below, print the logs of the web service and delete the service"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "service.delete()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deleted compute cluster\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    compute_cluster.delete()\n",
    "    print(\"Deleted compute cluster\")\n",
    "except ComputeTargetException:\n",
    "    print(\"Compute Cluster Not found\")"
   ]
  }
 ],
 "metadata": {
  "kernel_info": {
   "name": "python3-azureml"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  },
  "nteract": {
   "version": "nteract-front-end@1.0.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}