The following code produced an error on the transform function. The fit function works correctly. This error is reproduced for every feature in the original dataset. X = df.drop(["Target"], axis=1) y = df["Target"] ofe = OpenFE() ofe.fit(data=X, label=y, categorical_features=cat...
encoded_categorical_feature = encoding_layer(categorical_feature_layer) all_inputs = [numeric_feature_layer, categorical_feature_layer] encoded_features = [numeric_feature_layer, encoded_categorical_feature] concat_features = Concatenate()(encoded_features) output = Dense(units=1, activation='sigmoid'...
categorical, clear-cut, decided, definite, explicit, express, positive, precise, specific, unambiguous, unequivocal. 11. Freed from contact or connection: free.12. Containing nothing: bare, blank, empty, vacant, vacuous, void.verb1. To become brighter or fairer.Also used with up: ...
defcreate_estimator_spec(self,features,mode,logits,labels=None,train_op_fn=None):"""See `Head`."""withops.name_scope('head'):logits=head_lib._check_logits(logits,self.logits_dimension)# pylint:disable=protected-access# Predict.pred_keys=prediction_keys.PredictionKeyswithops.name_scope(None,'...
epitab — Tables for epidemiologists 5 tabodds is used with case – control and cross-sectional data. It tabulates the odds of failure against a categorical explanatory variable expvar. If expvar is specified, tabodds performs an approximate χ2 test of homogeneity of odds and a test for ...
(self, model, initialization_examples, explainable_model, explainable_model_args, is_function, augment_data, max_num_of_augmentations, explain_subset, features, classes, transformations, allow_all_transformations, shap_values_output, categorical_features, model_task, reset_index, **kwargs) 302 ...