modules/ml/src/main/java/org/apache/ignite/ml/preprocessing/normalization/NormalizationTrainer.java

   1 /*
   2  * Licensed to the Apache Software Foundation (ASF) under one or more
   3  * contributor license agreements.  See the NOTICE file distributed with
   4  * this work for additional information regarding copyright ownership.
   5  * The ASF licenses this file to You under the Apache License, Version 2.0
   6  * (the "License"); you may not use this file except in compliance with
   7  * the License.  You may obtain a copy of the License at
   8  *
   9  *      http://www.apache.org/licenses/LICENSE-2.0
  10  *
  11  * Unless required by applicable law or agreed to in writing, software
  12  * distributed under the License is distributed on an "AS IS" BASIS,
  13  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  14  * See the License for the specific language governing permissions and
  15  * limitations under the License.
  16  */
  17
  18 package org.apache.ignite.ml.preprocessing.normalization;
  19
  20 import org.apache.ignite.ml.dataset.DatasetBuilder;
  21 import org.apache.ignite.ml.math.Vector;
  22 import org.apache.ignite.ml.math.functions.IgniteBiFunction;
  23 import org.apache.ignite.ml.preprocessing.PreprocessingTrainer;
  24
  25 /**
  26  * Trainer of the Normalization preprocessor.
  27  *
  28  * @param <K> Type of a key in {@code upstream} data.
  29  * @param <V> Type of a value in {@code upstream} data.
  30  */
  31 public class NormalizationTrainer<K, V> implements PreprocessingTrainer<K, V, Vector, Vector> {
  32     /**  Normalization in L^p space. Must be greater than 0. Default value is 2. */
  33     private int p = 2;
  34
  35     /** {@inheritDoc} */
  36     @Override public NormalizationPreprocessor<K, V> fit(DatasetBuilder<K, V> datasetBuilder,
  37         IgniteBiFunction<K, V, Vector> basePreprocessor) {
  38         return new NormalizationPreprocessor<>(p, basePreprocessor);
  39     }
  40
  41     /**
  42      * Gets the degree of L space parameter value.
  43      * @return The parameter value.
  44      */
  45     public double p() {
  46         return p;
  47     }
  48
  49     /**
  50      * Sets the p parameter value. Must be greater than 0.
  51      *
  52      * @param p The given value.
  53      * @return The Normalization trainer.
  54      */
  55     public NormalizationTrainer<K, V> withP(int p) {
  56         assert p > 0;
  57         this.p = p;
  58         return this;
  59     }
  60 }