Fall detection using Machine Learning

The aim of this project is to study the performance of several machine learning algorithms in automatically detecting falls thanks to the indicators provided. To achieve this, we will follow the following steps using Python programming: Naive Bayes- Naive Bayes Classifier – LDA : Linear Discriminant Analysis – QDA: Quadratic Discriminant Analysis – Logistic regression – KNN- K nearest neighbors – Decision Tree- Decision Tree – Random Forest– AdaBoost – Gradient Boosting.