ValueError: X has 23 features per sample; expecting 16

@sarika77 wrote:

predic=logreg.predict(x_test)

ValueError Traceback (most recent call last)
in
----> 1 predic=logreg.predict(x_test)

~\Anaconda3\lib\site-packages\sklearn\linear_model\base.py in predict(self, X)
287 Predicted class label per sample.
288 “”"
–> 289 scores = self.decision_function(X)
290 if len(scores.shape) == 1:
291 indices = (scores > 0).astype(np.int)

~\Anaconda3\lib\site-packages\sklearn\linear_model\base.py in decision_function(self, X)
268 if X.shape[1] != n_features:
269 raise ValueError(“X has %d features per sample; expecting %d”
–> 270 % (X.shape[1], n_features))
271
272 scores = safe_sparse_dot(X, self.coef_.T,

ValueError: X has 23 features per sample; expecting 16

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