Implementation of Linear Regression Predictor

The preprocessing stage:

• Removes the pace column
• Filters out unknown genders
• Removes the 2013 data
• Converts the time to a numerical format
• Organizes the ages into group ranges
• Removes duplicates among years by averaging their results

In order to generate the data for Y1-naive bayes:

python generate-naive.py

In order to generate the data for Y1-logistic regression:

python generate-logistic.py

In order to generate the data for Y2:

python generate_Y2.py

In order to generate the data for futrue Prediction:

python generate_PREDICTION.py

The files training_x.csv, training_y.csv, test_x.csv and test_y.csv must be available from the generate Y1-logistic step.

python LogisticRegression.py

The files train_x.csv, train_y.csv, test_x.csv and test_y.csv must be available from the generate Y1-naive step.

python naive_bayes.py

The files Y2Y_train.csv, Y2Y_test.csv, Y2X_test.csv, Y2X_train.csv must be avilable from the generate Y2 step.

python linear_regression.py