ValueError: Found array with 0 sample(s) (shape=(0, 5)) while a minimum of 2 is required by LinearDiscriminantAnalysis.

[dhruvjm]

File name : intraday_ml_model_fit

`Importing and creating CSV DataFrame... Preprocessing data... Creating train/test split of data... Fitting classifier model...

ValueError Traceback (most recent call last)

in () 177 178 #model.fit(X_train, y_train) --> 179 model.fit(X, y) 180 print("Outputting metrics...") 181 print("Hit-Rate: %s" % model.score(X_test, y_test)) ~\Anaconda3\lib\site-packages\sklearn\discriminant_analysis.py in fit(self, X, y) 427 Target values. 428 """ --> 429 X, y = check_X_y(X, y, ensure_min_samples=2, estimator=self) 430 self.classes_ = unique_labels(y) 431 ~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_X_y(X, y, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, warn_on_dtype, estimator) 571 X = check_array(X, accept_sparse, dtype, order, copy, force_all_finite, 572 ensure_2d, allow_nd, ensure_min_samples, --> 573 ensure_min_features, warn_on_dtype, estimator) 574 if multi_output: 575 y = check_array(y, 'csr', force_all_finite=True, ensure_2d=False, ~\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator) 460 " minimum of %d is required%s." 461 % (n_samples, shape_repr, ensure_min_samples, --> 462 context)) 463 464 if ensure_min_features > 0 and array.ndim == 2: ValueError: Found array with 0 sample(s) (shape=(0, 5)) while a minimum of 2 is required by LinearDiscriminantAnalysis. ` Why am I not able to fit the model? Is there something wrong with my CSV file?