I want to retrieve the features selected by forward sequential selection. Both the feature_names.shape and sfs_forward.get_support().shape are (1185,) but my code raised IndexError: boolean index did not match indexed array along dimension 0; dimension is 6 but corresponding boolean dimension is 1185.
from sklearn.preprocessing import StandardScaler
import numpy as np
import pandas as pd
from sklearn.feature_selection import SequentialFeatureSelector
X = df.iloc[:,:-1]
y = df.T.loc["subtype",:]
scaler = StandardScaler().fit(X)
X_scaled = scaler.transform(X)
X_scaled = X_scaled[~np.isnan(X_scaled).all(axis=1)]
feature_names = np.array(X.columns)
tic_fwd = time()
sfs_forward = SequentialFeatureSelector(
ridge, n_features_to_select=2, direction="forward"
).fit(X_scaled, y_transformed)
toc_fwd = time()
print(
"Features selected by forward sequential selection: "
f"{feature_names[sfs_forward.get_support()]}"
)
print(f"Done in {toc_fwd - tic_fwd:.3f}s")
Traceback:
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
Input In [27], in <cell line: 7>()
2 sfs_forward = SequentialFeatureSelector(
3 ridge, n_features_to_select=2, direction="forward"
4 ).fit(X_scaled, y_transformed)
5 toc_fwd = time()
7 print(
8 "Features selected by forward sequential selection: "
----> 9 f"{feature_names[sfs_forward.get_support()]}"
10 )
11 print(f"Done in {toc_fwd - tic_fwd:.3f}s")
IndexError: boolean index did not match indexed array along dimension 0; dimension is 6 but corresponding boolean dimension is 1185
feature_names.shape
(1185,)
sfs_forward.get_support().shape
(1185,)
Data:
df.iloc[0:20,0:20]
pd.DataFrame({'AAAS': {'TCGA.2K.A9WE.01A': 3.33370417925201,
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I had a similar problem under a similar setup. All I needed to do was call the
ravel()function to get a 1D rep of my output array. In your case, I would suggestfeature_names[sfs_forward.get_support()].ravel()