model.py

import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LinearRegression
import numpy as np
from sklearn.externals import joblib
from sklearn import model_selection

"""
Model
"""


def model_train():
    data = pd.read_csv('occurrences.csv')
    data = data.drop('date', axis=1)
    train_pr = ['barcelona', 'madrid', 'real', 'barça']
    prdata = data[train_pr]
    target = data.match

    predictor = LinearRegression(n_jobs=-1)
    predictor.fit(prdata, target)

    X_TEST = [[[20, 10, 5, 4]], [[10, 5, 4, 2]], [[5, 3, 2, 1]], [[0, 0, 0, 0]], [[100, 100, 100, 100]]]

    print("Test Values= barcelona, madrid, real, barça")
    for element in X_TEST:
        outcome = predictor.predict(X=element)
        coefficients = predictor.coef_
        print("Test Values: {0}, Outcome: {1}, Coefficient: {2}".format(element, outcome, coefficients))


if __name__ == "__main__":
    model_train()