001/*
002 * Copyright (c) 2015-2020, Oracle and/or its affiliates. All rights reserved.
003 *
004 * Licensed under the Apache License, Version 2.0 (the "License");
005 * you may not use this file except in compliance with the License.
006 * You may obtain a copy of the License at
007 *
008 *     http://www.apache.org/licenses/LICENSE-2.0
009 *
010 * Unless required by applicable law or agreed to in writing, software
011 * distributed under the License is distributed on an "AS IS" BASIS,
012 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express implied.
013 * See the License for the specific language governing permissions and
014 * limitations under the License.
015 */
016
017package org.tribuo;
018
019import com.oracle.labs.mlrg.olcut.provenance.Provenance;
020
021import java.util.Collections;
022import java.util.Map;
023
024/**
025 * Denotes this trainer emits a {@link SparseModel}.
026 */
027public interface SparseTrainer<T extends Output<T>> extends Trainer<T> {
028
029    /**
030     * Trains a sparse predictive model using the examples in the given data set.
031     * @param examples The data set containing the examples.
032     * @return A sparse predictive model that can be used to generate predictions for new examples.
033     */
034    @Override
035    default public SparseModel<T> train(Dataset<T> examples) {
036        return train(examples, Collections.emptyMap());
037    }
038
039    /**
040     * Trains a sparse predictive model using the examples in the given data set.
041     * @param examples the data set containing the examples.
042     * @param runProvenance Training run specific provenance (e.g., fold number).
043     * @return a predictive model that can be used to generate predictions for new examples.
044     */
045    @Override
046    public SparseModel<T> train(Dataset<T> examples, Map<String, Provenance> runProvenance);
047
048}