Using the ES algorithm to train RBF-network and implement regression and classification algorithms on the dataset
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Updated
Aug 25, 2020 - Python
Using the ES algorithm to train RBF-network and implement regression and classification algorithms on the dataset
Kaggle Machine Learning Competition Project : To classify activities into one of the six activities performed by individuals by reading the inertial sensors data collected using Smartphone.
evolutionary-based approach in RBF neural network training
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Using data mining techniques to predict if the organization is prone to bankruptcy using the data with 250 records and 6 nominal attributes per record. Machine learning techniques used: Linear and non-linear SVM, Decision Tree Classifier, Gaussian Naive Bayes.
Two pattern classification problem using Radial Basis Functions (RBF) Neural Networks, with center vectors selected via self-organizing map (SOM) neural networks.
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This repository describes the application of numerical Collocation method in Machine Learning as a Supervised learning algorithm
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