linmodel.py

import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error, r2_score


class LinModel:
    def __init__(self):
        pass

    def getResults(self):
        df = pd.read_csv('employee_data.csv')
        y = df.salary
        X = df.drop('salary', axis=1)
        X_train, X_test, y_train, y_test = train_test_split(X,
                                                            y,
                                                            test_size=0.2,
                                                            random_state=0)
        reg = LinearRegression().fit(X_train, y_train)
        y_pred = reg.predict(X_test)
        RMSE = pow(mean_squared_error(y_pred, y_test), 0.5)
        R = r2_score(y_pred, y_test)
        return reg, y_pred, RMSE, R

    def getCoef(self):
        return self.getResults()[0].coef_


def mainLinModel():
    cof = LinModel().getCoef()
    print(cof)