To achieve this numerous classification algorithm (Decision Tree, Random Forest, SVM, Neural Net, Naive Bayes, and others) from different machine learning libraries (Scikit-learn, ML.Net, Keras) are ...

Binary Classification of Epilepsy Using Classical Machine Learning Algorithms and Ensemble Learning Techniques Abstract: Epilepsy is a neurological disorder characterized by recurrent seizures.

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. ... Support Vector Machines, aka SVM (for binary classification) ...

This repository contains a binary classification project focused on predicting machine failures using deep learning techniques. The project uses Keras with TensorFlow as a backend. The goal is to ...

This project presents a methodical approach to classifying DNA sequences leveraging machine learning techniques 🤖. It includes the journey from raw data preprocessing to the evaluation of several ...

Dr. James McCaffrey of Microsoft Research uses code samples and screen shots to explain perceptron classification, a machine learning technique that can be used for predicting if a person is male or ...

SWELL-KW Dataset. The results of different supervised and unsupervised learning algorithms using the SWELL-KW dataset are illustrated in Tables 4A,B, 5.The highest classification accuracy achieved ...