linearRegresion.py 文件源码

def linear_model_multivariate():
    #coefficient = (X_trans*X)^-1 * X_trans * y 

    data = pd.read_csv('E://Spyder/LinearRegression/data/data.csv')
    X_tem = []
    Y_tem = []
    linearModel={}
    for X_data ,Y_data in zip(data['x'],data['y']):
        X_tem.append(int(X_data))
        Y_tem.append(float(Y_data))
    X_parameters = np.ones((len(X_tem),2))

    for i in range(len(X_tem)):
        X_parameters[i][0] = X_tem[i]

    Y_parameters = np.array(Y_tem)
    # Formula  
    # coefficient = inv(X.T*X) * X.T * y    
    coefficient = np.dot(np.dot(np.linalg.inv(np.dot(X_parameters.T,X_parameters)),X_parameters.T),Y_parameters)

    avg_X = X_parameters.mean(axis = 0)   
    intercept = Y_parameters.mean() + coefficient * avg_X[1]
    linearModel['coefficient'] = coefficient
    linearModel['intercept'] = intercept
    return linearModel