Description

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House price prediction data using linier regression by using data with www.kaggel.com obtained 4600 data and 18 variables

Then check the information data to find out the data type and whether there is a null value

Displays an example of 10 rows of data display

Displays variable data

Data yang tidak digunakan di drop, sehingga hanya 4 fariabel yang digunakan antara lain bedrooms, sqft_living, sqft_living, sqft_lot, and floors

Then divide the data into train data and test data

Import module Liner Regression and creating an object Linear Regression Class and Fittig the training data

At this stage, it produces a prediction price that is accommodated in the y prediction variable

The evaluation results show that linear regression can predict house prices based on bedrooms, sqft_living, sqft_living, sqft_lot, and floors with prediction results ;

r2 socre is 0.029636662761839516
mean_sqrd_error is== 989621498036.9012
root_mean_squared error of is== 994797.2145301278