<s> """<STR_LIT>""" <EOL> print ( __doc__ ) <EOL> import numpy as np <EOL> from sklearn . svm import SVR <EOL> import matplotlib . pyplot as plt <EOL> X = np . sort ( <NUM_LIT:5> * np . random . rand ( <NUM_LIT> , <NUM_LIT:1> ) , axis = <NUM_LIT:0> ) <EOL> y = np . sin ( X ) . ravel ( ) <EOL> y [ : : <NUM_LIT:5> ] += <NUM_LIT:3> * ( <NUM_LIT:0.5> - np . random . rand ( <NUM_LIT:8> ) ) <EOL> svr_rbf = SVR ( kernel = '<STR_LIT>' , C = <NUM_LIT> , gamma = <NUM_LIT:0.1> ) <EOL> svr_lin = SVR ( kernel = '<STR_LIT>' , C = <NUM_LIT> ) <EOL> svr_poly = SVR ( kernel = '<STR_LIT>' , C = <NUM_LIT> , degree = <NUM_LIT:2> ) <EOL> y_rbf = svr_rbf . fit ( X , y ) . predict ( X ) <EOL> y_lin = svr_lin . fit ( X , y ) . predict ( X ) <EOL> y_poly = svr_poly . fit ( X , y ) . predict ( X ) <EOL> lw = <NUM_LIT:2> <EOL> plt . scatter ( X , y , color = '<STR_LIT>' , label = '<STR_LIT:data>' ) <EOL> plt . hold ( '<STR_LIT>' ) <EOL> plt . plot ( X , y_rbf , color = '<STR_LIT>' , lw = lw , label = '<STR_LIT>' ) <EOL> plt . plot ( X , y_lin , color = '<STR_LIT:c>' , lw = lw , label = '<STR_LIT>' ) <EOL> plt . plot ( X , y_poly , color = '<STR_LIT>' , lw = lw , label = '<STR_LIT>' ) <EOL> plt . xlabel ( '<STR_LIT:data>' ) <EOL> plt . ylabel ( '<STR_LIT:target>' ) <EOL> plt . title ( '<STR_LIT>' ) <EOL> plt . legend ( ) <EOL> plt . show ( ) </s>
