/*
* Encog(tm) Core v3.4 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2016 Heaton Research, Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.ml.data;
/**
* An interface designed to abstract classes that store machine learning data.
* This interface is designed to provide EngineDataSet objects. These can be
* used to train machine learning methods using both supervised and unsupervised
* training.
*
* Some implementations of this interface are memory based. That is they store
* the entire contents of the dataset in memory.
*
* Other implementations of this interface are not memory based. These
* implementations read in data as it is needed. This allows very large datasets
* to be used. Typically the add methods are not supported on non-memory based
* datasets.
*
* @author jheaton
*/
public interface MLDataSet extends Iterable<MLDataPair> {
/**
* @return The size of the ideal data.
*/
int getIdealSize();
/**
* @return The size of the input data.
*/
int getInputSize();
/**
* @return True if this is a supervised training set.
*/
boolean isSupervised();
/**
* Determine the total number of records in the set.
*
* @return The total number of records in the set.
*/
long getRecordCount();
/**
* Read an individual record, specified by index, in random order.
*
* @param index
* The index to read.
* @param pair
* The pair that the record will be copied into.
*/
void getRecord(long index, MLDataPair pair);
/**
* Opens an additional instance of this dataset.
*
* @return The new instance.
*/
MLDataSet openAdditional();
/**
* Add a object to the dataset. This is used with unsupervised training, as
* no ideal output is provided. Note: not all implemenations support the add
* methods.
*
* @param data1
* The data item to be added.
*/
void add(MLData data1);
/**
* Add a set of input and ideal data to the dataset. This is used with
* supervised training, as ideal output is provided. Note: not all
* implementations support the add methods.
*
* @param inputData
* Input data.
* @param idealData
* Ideal data.
*/
void add(MLData inputData, MLData idealData);
/**
* Add a an object to the dataset. This is used with unsupervised training,
* as no ideal output is provided. Note: not all implementations support the
* add methods.
*
* @param inputData
* A MLDataPair object that contains both input and ideal data.
*/
void add(MLDataPair inputData);
/**
* Close this datasource and release any resources obtained by it, including
* any iterators created.
*/
void close();
int size();
MLDataPair get(int index);
}