SvmModel test¶
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test
(self, frame, label_column, observation_columns=None)¶ [ALPHA] Predict test frame labels and return metrics.
Parameters: frame : Frame
Frame whose labels are to be predicted.
label_column : unicode
Column containing the actual label for each observation.
observation_columns : list (default=None)
Column(s) containing the observations whose labels are to be predicted and tested. Default is to test over the columns the SVM model was trained on.
Returns: : dict
A dictionary with binary classification metrics. The data returned is composed of the following keys:
‘accuracy’ : doubleThe proportion of predictions that are correctly identified‘confusion_matrix’ : dictionaryA table used to describe the performance of a classification model‘f_measure’ : doubleThe harmonic mean of precision and recall‘precision’ : doubleThe proportion of predicted positive instances that are correctly identified‘recall’ : doubleThe proportion of positive instances that are correctly identified.Predict the labels for a test frame and run classification metrics on predicted and target labels.
Examples
See here for examples.