predict

method predict(X, verbose=None) [source]

Get class predictions on unseen data or rows in the dataset. New data is first transformed through the model's pipeline. Transformers that are only applied on the training set are skipped. If called from a trainer, the best model in the pipeline (under the winner attribute) is used. If called from a model, that model is used. The estimator must have a predict method.

Parameters:

X: int, str, slice, sequence or dataframe-like
Index names or positions of rows in the dataset, or unseen feature set with shape=(n_samples, n_features).

verbose: int or None, optional (default=None)
Verbosity level of the output. If None, it uses the transformer's own verbosity.

Returns:

np.array
Predicted targets with shape=(n_samples,).

Example

from atom import ATOMClassifier

atom = ATOMClassifier(X, y)
atom.run(["Tree", "AdaB"], metric="AP", n_calls=10)

# Make predictions on new data
predictions = atom.adab.predict(X_new)