Machine learning with R (RF, Adabost.M1, DT, NB, LR, NN)

Course details

• How to download and install R
  
• How to set your working directory import your data and detect rows containing missing values
  
• For binary classification

1. Training and prediction using the RandomForest model , prediction accuracy, Confusion matrix and confidence interval
2. Training and prediction using the Adabost.M1model , prediction accuracy, Confusion matrix and confidence interval
3. Training and prediction using the Decision Tree model , prediction accuracy, Confusion matrix and confidence interval
4. Training and prediction using the logistic regression model, prediction accuracy, confusion matrix and confidence interval
5. Training and prediction using the Naive Bayes model, prediction accuracy, confusion matrix and confidence interval
6. Training and prediction using the Neural Network model , prediction accuracy, confusion matrix and confidence interval
7. Training and prediction using the Convolutional neural network (KNN) , prediction accuracy, confusion matrix and confidence interval

• How to combine models to predict
• Missing values treatment ,variables selection and prediction using a linear regression model
• K mean Clustering