Description : Worked with a dataset containing only categorical variables of 23 categorical feature in which it was to be predicted using the features whether the mushroom is edible or not.
Language: R
Approach: EDA and feature engineering was done to extract the important features that was used for modelling. Accuracy of each algorithm was compared and the best model was selected.
Algorithm used: Logistic Regression, Decision tree, Random Forest, Xgboost and SVM.
Encoding Techniques: one hot, Label, Leave one out and binary