09bfc1b3ef8494cf17a192bbe83df576ccdac86f,cesium/predict.py,,model_predictions,#,16

Before Change

        preds = model.predict(feature_df)

    if len(preds.shape) == 1:
        return pd.Series(preds, index=feature_df.index, name="prediction")
    else:
        if isinstance(model, GridSearchCV):
            columns = model.best_estimator_.classes_
        else:
            columns = model.classes_
        return pd.DataFrame(preds, index=feature_df.index, columns=columns)


def predict_data_files(ts_paths, features_to_use, model,
                       custom_features_script=None):

After Change

        else:
            columns = model.classes_
        predset["class_label"] = columns
        predset["prediction"] = (["name", "class_label"], preds)
    return predset

Instances