rdisipio · November 6, 2022 13:52
diff --git a/quickstart-9.py b/quickstart-9.py
 from sklearn.preprocessing import KBinsDiscretizer

 n_bins = 10 # the more, the merrier
 scaled_feature_names = [f"q_{x}" for x in feature_names]

 qt = KBinsDiscretizer(n_bins=n_bins, encode='ordinal', strategy='quantile')
 X_qt = qt.fit_transform(X).astype(np.int32)  # nb: bin number must be an integer
	from sklearn.preprocessing import KBinsDiscretizer

	n_bins = 10 # the more, the merrier
	scaled_feature_names = [f"q_{x}" for x in feature_names]

	qt = KBinsDiscretizer(n_bins=n_bins, encode='ordinal', strategy='quantile')
	X_qt = qt.fit_transform(X).astype(np.int32) # nb: bin number must be an integer