ML-model-implementations

Various Machine Learning model implementations in R

Part 1

Classification

• Logistic Regression
• Decision Tree
• Random Forests
• XG Boost (Extreme Gradient Boosting)
• Naive Bayes
• Support Vector Model(SVM)
• K-Nearest Neighbours (K-NN)

Regression

• Simple/Multiple Linear Regression
• Regression Trees

Part 2

Clustering

• K-Means
• Hierarchial

Tuning & Understanding the Model (stats & maths)

• Evaluation metrics
  • Accuracy and Kappa
  • RMSE and R^2
  • ROC (AUC, Sensitivity and Specificity)
  • LogLoss
• Hyperparameter Tuning for each model

Artificial Neural Networks

• MLP
• RNN
• CNN