sklearn-linear regression

Question 1

create an instance of linear regression

Answer 1

reg = LinearRegression()

Question 2

fit linear regression model

Answer 2

reg.fit(x_matrix,y)

Question 3

calculate R-squred for linear regression

Answer 3

reg.score(x_matrix,y)

Question 4

find intercept

Answer 4

reg.intercept_

Question 5

find coefficient

Answer 5

reg.coef_

Question 6

make prediction for new_data. new_data is one-dimensional

Answer 6

reg.predict([[new_data]])

Question 7

what you need to do if x is one dimensional ? give the code.

Answer 7

It needs to be a two-dimensional matrix.

x_matrix = x.values.reshape(-1,1)

Question 8

feature selection. code and its output?

Answer 8

f_regression(x,y)

Question 9

obtain pvalue from feature selection

Answer 9

p_values = f_regression(x,y)[1].round(3)

Question 10

Create a StandardScaler instance

Answer 10

scaler = StandardScaler()

Question 11

fit feature x to scaler/calculate the mean and std

Answer 11

scaler.fit(x)

Question 12

create a new variable for feature x with raw data scaled

Answer 12

x_scaled = scaler.transform(x)