Correction in "Testing and Training Sets" section #1
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Correction in "Testing and Training Sets" section, in: df=pd.DataFrame(dict(x=x[indexes],f=f[indexes],y=y[indexes])) from sklearn.cross_validation import train_test_split datasize=df.shape[0] #split dataset using the index, as we have x,f, and y that we want to split. itrain,itest = train_test_split(range(30),train_size=24, test_size=6) xtrain= df.x[indexes[itrain]].values ftrain = df.f[indexes[itrain]].values ytrain = df.y[indexes[itrain]].values xtest= df.x[indexes[itest]].values ftest = df.f[indexes[itest]].values ytest = df.y[indexes[itest]].values # Dict creates different indexing so in order for the itrain and itest indices to be correct they have to pass through 'indexes'!! # otherwise there's a lot of Nan values that should be there.
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Correction in "Testing and Training Sets" section, in:
df=pd.DataFrame(dict(x=x[indexes],f=f[indexes],y=y[indexes]))
from sklearn.cross_validation import train_test_split
datasize=df.shape[0]
#split dataset using the index, as we have x,f, and y that we want to split.
itrain,itest = train_test_split(range(30),train_size=24, test_size=6)
xtrain= df.x[indexes[itrain]].values
ftrain = df.f[indexes[itrain]].values
ytrain = df.y[indexes[itrain]].values
xtest= df.x[indexes[itest]].values
ftest = df.f[indexes[itest]].values
ytest = df.y[indexes[itest]].values
Dict creates different indexing so in order for the itrain and itest indices to be correct they have to pass through 'indexes'!!
otherwise there's a lot of Nan values that should be there.