index int64 | repo_id string | file_path string | content string |
|---|---|---|---|
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/dataset/SparseDyadRankingInstance.java | package ai.libs.jaicore.ml.ranking.dyad.dataset;
import java.util.ArrayList;
import java.util.Collection;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.NoSuchElementException;
import java.util.Set;
import java.util.stream.Collectors;
import org.api4.java.ai.ml.ranking.IR... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/Dyad.java | package ai.libs.jaicore.ml.ranking.dyad.learner;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.common.math.IVector;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
/**
* Represents a dyad consisting of an instance and an alternative, represented
* by f... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/ARandomlyInitializingDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.apache.commons.math3.stat.descriptive.SummaryStatistics;
imp... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/ActiveDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import org.api4.java.ai.ml.core.exception.TrainingException;
import ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.PLNetDyadRanker;
/**
* Abstract description of a pool-based active learning strategy for dyad
* ranking.
*
* @author Jonas Hanselle... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/DyadDatasetPoolProvider.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import org.api4.java.ai.ml.ranking.dyad.d... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/IDyadRankingPoolProvider.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import java.util.Collection;
import java.util.Set;
import org.api4.java.ai.ml.core.learner.active.IActiveLearningPoolProvider;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
im... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/PrototypicalPoolBasedActiveDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.api4.java.ai.ml.core.exception.TrainingException;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRank... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/RandomPoolBasedActiveDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.PLNetDyadRanker;
/**
* A random active dyad ranker. The sampling strategy picks a problem instance
* at random and then picks two alternatives at random for pairwise comparison.
* This is repeat... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/activelearning/UCBPoolBasedActiveDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.activelearning;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;
import org.api4.java.ai.ml.core.exception.TrainingException;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.r... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/IDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm;
import org.api4.java.ai.ml.core.learner.ISupervisedLearner;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/IPLDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm;
/**
* An abstract representation for a dyad ranker using Placket Luce models.
*
* @author Helena Graf
*
*/
public interface IPLDyadRanker extends IDyadRanker {
}
|
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/IPLNetDyadRankerConfiguration.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm;
import java.util.List;
import org.aeonbits.owner.Config.Sources;
import org.aeonbits.owner.Mutable;
@Sources({ "file:conf/plNet/plnet.properties" })
public interface IPLNetDyadRankerConfiguration extends Mutable {
/**
* The learning rate for the gradient ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/PLNetDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm;
import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.LinkedList;
import java.util.List;
import java.util.Set;
import org.aeonbits.owner.ConfigFactory;
import o... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/PLNetLoss.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.NDArrayIndex;
import org.nd4j.linalg.ops.transforms.Transforms;
/**
* Implements the negative log likelihood (NLL) loss function for PL networks... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/featuretransform/BiliniearFeatureTransform.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.featuretransform;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.common.math.IVector;
/**
* Implementation of the feature transformation method using the Kroenecker
* Product.
*
* @author Helena Graf, Mirko Jürgens
*
*/
publi... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/featuretransform/FeatureTransformPLDyadRanker.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.featuretransform;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.stream.Collectors;
import org.api4.java.ai.ml.core.exception.PredictionException;
import org.api4.java.ai.ml.core.exception.TrainingException;
import or... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/algorithm/featuretransform/IDyadFeatureTransform.java | package ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.featuretransform;
import java.util.HashMap;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/optimizing/BilinFunction.java | package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.common.math.IVector;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/optimizing/DyadRankingFeatureTransformNegativeLogLikelihood.java | package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.algorithm.IOptimizati... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/optimizing/DyadRankingFeatureTransformNegativeLogLikelihoodDerivative.java | package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.common.math.IVector;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/optimizing/IDyadRankingFeatureTransformPLGradientDescendableFunction.java | package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.common.math.IVector;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/optimizing/IDyadRankingFeatureTransformPLGradientFunction.java | package ai.libs.jaicore.ml.ranking.dyad.learner.optimizing;
import java.util.Map;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.common.math.IVector;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/search/ADyadRankedNodeQueue.java | package ai.libs.jaicore.ml.ranking.dyad.learner.search;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Iterator;
import java.util.List;
import java.util.Queue;
import org.api4.java.ai.graphsearch.problem.pathsearch.pathevaluation.IEvaluatedPath;
import org.api4.java... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/search/ADyadRankedNodeQueueConfig.java | package ai.libs.jaicore.ml.ranking.dyad.learner.search;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.ObjectInputStream;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import ai.libs.jaicore.ml.ranking.dyad.learner.algorithm.IDyadRanker;
import ai.libs.jaic... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/search/RandomlyRankedNodeQueue.java | package ai.libs.jaicore.ml.ranking.dyad.learner.search;
import java.util.LinkedList;
import java.util.Random;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import ai.libs.jaicore.search.model.travesaltree.BackPointerPath;
/**
* A node queue for the best first search that inserts new nodes at a random
*... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/search/RandomlyRankedNodeQueueConfig.java | package ai.libs.jaicore.ml.ranking.dyad.learner.search;
import java.io.IOException;
import ai.libs.jaicore.search.algorithms.standard.bestfirst.BestFirst;
import ai.libs.jaicore.search.probleminputs.GraphSearchWithSubpathEvaluationsInput;
/**
* Configuration for a {@link RandomlyRankedNodeQueue}
*
* @author Hele... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/util/AbstractDyadScaler.java | package ai.libs.jaicore.ml.ranking.dyad.learner.util;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.math3.stat.descriptive.SummaryStatistics;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingD... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/util/DyadMinMaxScaler.java | package ai.libs.jaicore.ml.ranking.dyad.learner.util;
import java.text.DecimalFormat;
import java.util.List;
import org.apache.commons.math3.stat.descriptive.SummaryStatistics;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/util/DyadStandardScaler.java | package ai.libs.jaicore.ml.ranking.dyad.learner.util;
import java.util.List;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.common.math.IVector;
/**
* A scaler that can be fit to a certain dataset and then be used to standardize
* datasets, i.e. transform the data to have a mean of 0 a... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/util/DyadUnitIntervalScaler.java | package ai.libs.jaicore.ml.ranking.dyad.learner.util;
import java.util.List;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyad;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingDataset;
import org.api4.java.ai.ml.ranking.dyad.dataset.IDyadRankingInstance;
import org.api4.java.common.math.IVector;
/**
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot/inputoptimization/InputOptimizerLoss.java | package ai.libs.jaicore.ml.ranking.dyad.learner.zeroshot.inputoptimization;
import org.nd4j.linalg.api.ndarray.INDArray;
public interface InputOptimizerLoss {
public double loss(INDArray plNetOutput);
public double lossGradient(INDArray plNetOutput);
}
|
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot/inputoptimization/NegIdentityInpOptLoss.java | package ai.libs.jaicore.ml.ranking.dyad.learner.zeroshot.inputoptimization;
import org.nd4j.linalg.api.ndarray.INDArray;
/**
* Loss function for PLNet input optimization that maximizes the output of a PLNet. (i.e. minimizes the negative output)
* @author Michael Braun
*
*/
public class NegIdentityInpOptLoss imple... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot/inputoptimization/PLNetInputOptimizer.java | package ai.libs.jaicore.ml.ranking.dyad.learner.zeroshot.inputoptimization;
import org.deeplearning4j.nn.gradient.Gradient;
import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.indexing.BooleanIndexing;
impor... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/dyad/learner/zeroshot/util/InputOptListener.java | package ai.libs.jaicore.ml.ranking.dyad.learner.zeroshot.util;
import java.util.ArrayList;
import java.util.List;
import org.nd4j.linalg.api.ndarray.INDArray;
public class InputOptListener {
private int[] indicesToWatch;
private List<INDArray> inputList;
private List<Double> outputList;
public InputOptLi... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/filter/PairWisePreferenceToBinaryClassificationFilter.java | package ai.libs.jaicore.ml.ranking.filter;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core.filter.FilterApplicationFailedException;
import org.api4.java.ai.ml.core.filter.unsupervised.IUnsupervisedF... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/filter/package-info.java | package ai.libs.jaicore.ml.ranking.filter; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/package-info.java |
/**
* Label ranking package.
*
* @author mwever
*
*/
package ai.libs.jaicore.ml.ranking.label; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/IConfigurableLabelRanker.java | package ai.libs.jaicore.ml.ranking.label.learner;
public interface IConfigurableLabelRanker {
}
|
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/IGroupBasedRanker.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased;
import org.api4.java.ai.ml.ranking.dataset.IRankingDataset;
import org.api4.java.ai.ml.ranking.dataset.IRankingInstance;
import org.api4.java.ai.ml.ranking.learner.IRanker;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.Ranki... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/IGroupBuilder.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased;
import java.util.List;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.Group;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.ProblemInstance;
/**
* IGroupBuilder discribes the act of building gr... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/IGroupSolutionRankingSelect.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.Group;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.RankingForGroup;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.T... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/candidateprovider/IRankedSolutionCandidateProvider.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.candidateprovider;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.ProblemInstance;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.Ranking;
public interface IRankedSolutionCandidateProvider<I,S> {
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/Group.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
import java.util.List;
/**
* Group.java - Stores a group with it center as ID and the associated instances
*
* @author Helen Bierling
*
* @param <C>
* The identifier of the group
* @param <I>
* The instances i... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/GroupIdentifier.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
/**
* @author Helen Beierling
*
* @param <C> An identifier of a group
*/
public class GroupIdentifier<C> {
private C identifier;
public GroupIdentifier(final C id){
this.identifier = id;
}
public C getIdentifier(){
return this... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/ProblemInstance.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
public class ProblemInstance<I> {
/**
* @author Helen Beierling
*
* @param <I> stands for the observed instance
*/
private I instance;
public ProblemInstance() {}
public ProblemInstance(I inst) {
this.instance = inst;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/Ranking.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Map;
import org.api4.java.ai.ml.ranking.IRanking;
public class Ranking<O> extends ArrayList<O> implements IRanking<O> {
private static final long serialVersionUID... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/RankingForGroup.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
import java.util.List;
/**
* RankingForGroup.java - saves a solution ranking for a group identified by thier group
*
* @author Helen Beierling
*
* @param <C> The identifier of the group
* @param <O> The solutions that are ranked best... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/customdatatypes/Table.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes;
import java.util.ArrayList;
import java.util.HashMap;
import ai.libs.jaicore.basic.sets.Pair;
/**
* Table.java - This class is used to store probleminstance and their according solutions and
* performances for that solution.
*
* @auth... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/datamanager/IInstanceCollector.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.datamanager;
import java.util.List;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.ProblemInstance;
public interface IInstanceCollector <I>{
List<ProblemInstance<I>> getProblemInstances();
}
|
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/label/learner/clusterbased/datamanager/ITableGeneratorandCompleter.java | package ai.libs.jaicore.ml.ranking.label.learner.clusterbased.datamanager;
import java.util.List;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.ProblemInstance;
import ai.libs.jaicore.ml.ranking.label.learner.clusterbased.customdatatypes.Table;
public interface ITableGeneratorandComple... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/ARankingPredictionPerformanceMeasure.java | package ai.libs.jaicore.ml.ranking.loss;
import java.util.List;
import java.util.OptionalDouble;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.ranking.IRanking;
import org.api4.java.ai.ml.ranking.loss.IRankingPredictionPerformanceMeasure;
import ai.libs.jaicore.ml.classification.loss.dataset.APredict... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/KendallsTauDyadRankingLoss.java | package ai.libs.jaicore.ml.ranking.loss;
import org.api4.java.ai.ml.ranking.IRanking;
import org.api4.java.ai.ml.ranking.loss.IRankingPredictionPerformanceMeasure;
/**
* Computes the rank correlation measure known as Kendall's tau coefficient, i.e.
* (C - D) / (K * (K-1) /2), where C and D are the number of concord... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/KendallsTauOfTopK.java | package ai.libs.jaicore.ml.ranking.loss;
import java.util.List;
import java.util.OptionalDouble;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.ranking.IRanking;
import org.api4.java.ai.ml.ranking.loss.IRankingPredictionPerformanceMeasure;
/**
* Calculates the kendalls-tau loss only for the top k dya... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/NDCGLoss.java | package ai.libs.jaicore.ml.ranking.loss;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.OptionalDouble;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.ranking.IRanking;
import org.api4.java.ai.ml.ranking.loss.IRankingPredictionPerformanceMeasure;
/**
* The Nor... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/TopKOfPredicted.java | package ai.libs.jaicore.ml.ranking.loss;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.ranking.IRanking;
import org.api4.java.ai.ml.ranking.loss.IRankingPredictionPerformanceMeasure;
/**
* Calculates if the top-k dyads of the predicted ranking match the top-k dyads
* of the actual r... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/loss/package-info.java | package ai.libs.jaicore.ml.ranking.loss; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/ranking/object/package-info.java |
/**
* Object-Ranking package.
*
* @author mwever
*/
package ai.libs.jaicore.ml.ranking.object; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/package-info.java | package ai.libs.jaicore.ml.regression; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/learner/ConstantRegressor.java | package ai.libs.jaicore.ml.regression.learner;
import java.util.ArrayList;
import java.util.List;
import java.util.Objects;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core.evaluation.IPrediction;
i... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/learner/package-info.java | package ai.libs.jaicore.ml.regression.learner; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/learner | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/learner/perceptron/package-info.java | package ai.libs.jaicore.ml.regression.learner.perceptron; |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/ERegressionPerformanceMeasure.java | package ai.libs.jaicore.ml.regression.loss;
import java.util.List;
import org.api4.java.ai.ml.core.evaluation.IPredictionAndGroundTruthTable;
import org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/ERulPerformanceMeasure.java | package ai.libs.jaicore.ml.regression.loss;
import java.util.List;
import org.api4.java.ai.ml.core.evaluation.IPredictionAndGroundTruthTable;
import org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/ARegressionMeasure.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import org.api4.java.ai.ml.core.evaluation.supervised.loss.IDeterministicPredictionPerformanceMeasure;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.ml.classification.loss.dataset.APredictionPerformanceMeasure;
publi... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/AUnboundedRegressionMeasure.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
public abstract class AUnboundedRegressionMeasure extends ARegressionMeasure {
@Override
public double loss(final List<? extends Double> expected, final List<? extends... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/AbsoluteError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class AbsoluteError extends ARegressionMeasure... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/AsymmetricLoss.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class AsymmetricLoss extends ARegressionMeasure {
private double dividerOverestimation ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/AsymmetricLoss2.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
public class AsymmetricLoss2 extends ARegressionMeasure {
private double dividerUnderestimation = 10;
private double dividerOverestimation = 13;
public AsymmetricLos... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/LinearMeanSquaredError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class LinearMeanSquaredError extends AUnboundedRegressionMeasure {
private double weigh... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanAbsoluteError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
import ai.libs.jaicore.ml.regression.loss.instance.Abs... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanAbsolutePercentageError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class MeanAbsolutePercentageError extends ARegressionMeasure {
@Override
public double... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanAsymmetricLoss2.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class MeanAsymmetricLoss2 extends ARegressionMeasure {
private double dividerUnderestim... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanPercentageError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class MeanPercentageError extends ARegressionMeasure {
@Override
public double loss(fi... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanSquaredError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
import ai.libs.jaicore.ml.regression.loss.instance.Squ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanSquaredLogarithmicError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
import ai.libs.jaicore.ml.regression.loss.instance.Squ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanSquaredLogarithmicMeanSquaredError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class MeanSquaredLogarithmicMeanSquaredError extends AUnboundedRegressionMeasure {
@Ove... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/MeanSquaredPercentageError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class MeanSquaredPercentageError extends ARegressionMeasure {
@Override
public double ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/QuadraticQuadraticError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class QuadraticQuadraticError extends AUnboundedRegressionMeasure {
private double weig... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/R2.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
/**
* The R^2, aka. the coefficient of determination describes the proportion of the variance in the target variable and the predicted values.
* The formula of R^2 is a... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/RootMeanSquaredError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
/**
* The root mean squared loss function.
* This loss function computes the sum of differences of expected/actual pairs,
* divides this by the number of observations,... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/RootMeanSquaredLogarithmError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
public class RootMeanSquaredLogarithmError extends ARegressionMeasure {
public RootMeanSquaredLogarithmError() {
super();
}
@Ove... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/SquaredError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.List;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class SquaredError extends ARegressionMeasure ... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/WeightedAbsoluteError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class WeightedAbsoluteError extends AUnboundedRegressionMeasure {
private double weight... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/dataset/WeightedAsymmetricAbsoluteError.java | package ai.libs.jaicore.ml.regression.loss.dataset;
import java.util.ArrayList;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.basic.StatisticsUtil;
public class WeightedAsymmetricAbsoluteError extends AUnboundedRegressionMeasure {
private dou... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/instance/AbsoluteError.java | package ai.libs.jaicore.ml.regression.loss.instance;
import ai.libs.jaicore.ml.classification.loss.instance.AInstanceMeasure;
public class AbsoluteError extends AInstanceMeasure<Double, Double> {
@Override
public double loss(final Double expected, final Double predicted) {
return Math.abs(expected - predicted);
... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/instance/SquaredError.java | package ai.libs.jaicore.ml.regression.loss.instance;
import ai.libs.jaicore.ml.classification.loss.instance.AInstanceMeasure;
/**
* Measure computing the squared error of two doubles. It can be used to compute the mean squared error.
*
* @author mwever
*/
public class SquaredError extends AInstanceMeasure<Double,... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/loss/instance/SquaredLogarithmicError.java | package ai.libs.jaicore.ml.regression.loss.instance;
import ai.libs.jaicore.ml.classification.loss.instance.AInstanceMeasure;
public class SquaredLogarithmicError extends AInstanceMeasure<Double, Double> {
private static final double DEF_EPSILON = 1E-15;
private final double epsilon;
public SquaredLogarithmicEr... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/singlelabel/SingleTargetRegressionPrediction.java | package ai.libs.jaicore.ml.regression.singlelabel;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import ai.libs.jaicore.ml.core.evaluation.Prediction;
public class SingleTargetRegressionPrediction extends Prediction implements IRegressionPrediction {
public SingleTargetRegressionPredictio... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/regression/singlelabel/SingleTargetRegressionPredictionBatch.java | package ai.libs.jaicore.ml.regression.singlelabel;
import java.util.ArrayList;
import java.util.Collection;
import java.util.List;
import org.api4.java.ai.ml.regression.evaluation.IRegressionPrediction;
import org.api4.java.ai.ml.regression.evaluation.IRegressionResultBatch;
public class SingleTargetRegressionPredic... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/AScikitLearnWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Objects;
imp... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/IScikitLearnWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.IOException;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core.exception.TrainingException;
import org.api4.java.ai.ml.co... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/IScikitLearnWrapperConfig.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import org.aeonbits.owner.Config.Sources;
import ai.libs.python.IPythonConfig;
@Sources({ "file:conf/scikitlearn_wrapper.properties" })
public interface IScikitLearnWrapperConfig extends IPythonConfig {
public static final String K_TEMP_FOLDER = "skle... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnClassificationWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import org.api4.java.ai.ml.classification.singlelabel.evaluation.ISingleLabelClassification;
import org.api4.java.ai.ml.classification.singlelabel.evaluation.ISingleLab... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnMultiTargetRegressionWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnRegressionWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.IOException;
import java.util.List;
import java.util.stream.Collectors;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnTimeSeriesFeatureEngineeringWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.io.IOException;
import java.util.Objects;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledDataset;
import org.api4.java.ai.ml.core.dataset.supervised.ILabeledInstance;
import org.api4.java.ai.ml.core.evaluation.IPrediction;
import o... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnTimeSeriesRegressionWrapper.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.IOException;
import org.api4.java.ai.ml.core.evaluation.IPrediction;
import org.api4.java.ai.ml.core.evaluation.IPredictionBatch;
import ai.libs.jaicore.ml.core.EScikitLearnProblemType;
public class ScikitLearnTimeSeriesRegressionWrapper<P extends IPrediction... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnWrapperCommandBuilder.java | package ai.libs.jaicore.ml.scikitwrapper;
import java.io.File;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Objects;
import java.util.StringJoiner;
import org.api4.java.algorithm.Timeout;
import org.slf4j.Logger;
import ai.libs.jaicore.processes.EOperatingSystem;
impor... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/ScikitLearnWrapperExecutionFailedException.java | package ai.libs.jaicore.ml.scikitwrapper;
import org.api4.java.algorithm.exceptions.AlgorithmException;
public class ScikitLearnWrapperExecutionFailedException extends AlgorithmException {
private static final long serialVersionUID = -3658570286117660941L;
/**
* Creates a new {@link ScikitLearnWrapperExecutionF... |
0 | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper | java-sources/ai/libs/jaicore-ml/0.2.7/ai/libs/jaicore/ml/scikitwrapper/simple/ASimpleScikitLearnWrapper.java | package ai.libs.jaicore.ml.scikitwrapper.simple;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import org.aeonbits.owner.ConfigFactory;
import org.api4.j... |
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