from sklearn import svm

import numpy as np # linear algebra

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

df = pd.read_csv('../input/pitching.csv')
df

df_sg = df[df.gs == df.g]

Y = df_sg.w / df_sg.gs

Y_class = np.floor(Y)

clf = svm.SVC()
clf.fit(X, Y_class)