MSBD5001-Individual

In-class Kaggle Competition of MSBD5001 Fall 2019

##Main Features in 3 files:

1. Genres, Review-Ratio, Purhcase-date

2. Tags,Review-Ratio,Positive-reviews, purhcase-release interval

3. Categories,Review-ratio,Purchase-date

Models used at the moment:

1. RandomForest

2. AdaBoost

3. XgBoost

4 .BaggingRegressor

#Tuning:

1. GridSeachCV

2. PCA

#Language: Python

#Necessary Packages:

1.Pandas

2.Numpy

3.sklearn.ensemble

4.sklearn.decomposition

##How to Run:

-run the necessary jupyter notebook files and the output will be generated to the submission folder