<s> import numpy as np <EOL> from sklearn . datasets import load_boston <EOL> from sklearn . linear_model import LinearRegression <EOL> from matplotlib import pyplot as plt <EOL> boston = load_boston ( ) <EOL> x = boston . data <EOL> y = boston . target <EOL> lr = LinearRegression ( ) <EOL> lr . fit ( x , y ) <EOL> rmse = np . sqrt ( lr . residues_ / len ( x ) ) <EOL> print ( '<STR_LIT>' . format ( rmse ) ) <EOL> fig , ax = plt . subplots ( ) <EOL> ax . plot ( [ <NUM_LIT:0> , <NUM_LIT:50> ] , [ <NUM_LIT:0> , <NUM_LIT:50> ] , '<STR_LIT:->' , color = ( <NUM_LIT> , <NUM_LIT> , <NUM_LIT> ) , lw = <NUM_LIT:4> ) <EOL> ax . scatter ( lr . predict ( x ) , boston . target ) <EOL> ax . set_xlabel ( '<STR_LIT>' ) <EOL> ax . set_ylabel ( '<STR_LIT>' ) <EOL> fig . savefig ( '<STR_LIT>' ) </s>
