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Decision Tree classifier from scratch without any machine learning libraries
Implementing decision tree using ID3 algorithm based on Information Gain and using post pruning for improving accuracy
The objective of this project is to understand and implement the most commonly used Tree-pruning methods, Pre-pruning and Post-pruning.
Compilation of different ML algorithms implemented from scratch (and optimized extensively) for the courses COL774: Machine Learning (Spring 2020) & COL772: Natural Language Processing (Fall 2020)
Used ANOVA to choose the best features and Decision Tree with Post-Pruning to Predict Mortality of Covid-19 Patients