Website Prediksi Penyakit jantung dengan 5 fitur menggunakan metode KNN,bagging classifier,random forest
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Updated
Dec 5, 2022 - Python
Website Prediksi Penyakit jantung dengan 5 fitur menggunakan metode KNN,bagging classifier,random forest
This project predicts wind turbine failure using numerous sensor data by applying classification based ML models that improves prediction by tuning model hyperparameters and addressing class imbalance through over and under sampling data. Final model is productionized using a data pipeline
Customer Churn Prediction using Machine Learning and Deep learning. With Integration of MLFlow
The project is to analyze the flight booking dataset obtained from a platform which is used to book flight tickets.
R | Classification Project
Bagging is the term from "Bootstrap Aggregation Algorithm", That is for Low Bias & Low Variance
Drug consumption prediction models are like crystal balls for public health. By analyzing vast amounts of data, these models can identify individuals or communities at higher risk of drug use. They consider factors like demographics, social media activity, prescription history, and even economic indicators.
Diyabet Tespiti Projesi 💉
Data Mining Machine Learning | Assignments | JAN-APR 2023 | CMI
This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.
Machine Learning
The Office of Foreign Labor Certification is facing a dramatic increase in work visa applications, but is hampered by a sluggish review system. It needs to improve the process by developing a way to quickly, accurately identify applications likely to be accepted or rejected so their processing may be prioritized.
Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.
Comparative Analysis of Decision Tree Algorithms in Number Classification: Bagging vs. Random Forest vs. Gradient Boosting Decision Tree Classifiers
I applied the bagging and boosting methods using the decision tree as the base predictor on the sklearn’s breast cancer data set. I experiment with different parameters and report the results obtained.
In simple, a Loan (borrowing money from a bank) is the sum of money that you borrow from the bank or lending financial institution in order to meet needs. These needs could result from planned or unplanned events, and by borrowing, you incur a debt that you have to pay within the agreed duration on your contract.
The project contains an implementation of Bagging Classifier from scratch without the use of any inbuilt libraries.
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