**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