- EAST - Static variable in class org.ai_heuristic.util.TextConst
-
- EFC - Static variable in class org.ai_heuristic.util.AiHeuristicConst
-
The exponential factor c value
- EFN - Static variable in class org.ai_heuristic.util.AiHeuristicConst
-
The exponential factor n value
- ELEMENT - Static variable in class org.ai_heuristic.util.AiTypeConst
-
Defines an Element class parameter type
- ENDJAR - Static variable in class org.ai_heuristic.util.TextConst
-
Defines a file prefix
- Entropy - Class in org.ai_heuristic.algo.prob
-
This class implements a discrete Entropy evaluation.
- Entropy() - Constructor for class org.ai_heuristic.algo.prob.Entropy
-
Create a new instance of Entropy.
- Entropy(String) - Constructor for class org.ai_heuristic.algo.prob.Entropy
-
Create a new instance of Entropy.
- EQ - Static variable in class org.ai_heuristic.util.AiHeuristicConst
-
This defines the equal to comparison
- equals(Object) - Method in class org.ai_heuristic.algo.cluster.som.topology.Coords
-
Indicates whether some other object is "equal to" Coords class..
- EQUALS - Static variable in class org.ai_heuristic.util.TextConst
-
This defines the equal to comparison
- EuclideanDistance - Class in org.ai_heuristic.functs.metric
-
This measures the Euclidean Distance between two lists of objects.
- EuclideanDistance() - Constructor for class org.ai_heuristic.functs.metric.EuclideanDistance
-
Create a new instance of EuclideanDistance.
- EuclideanDistance(String) - Constructor for class org.ai_heuristic.functs.metric.EuclideanDistance
-
Create a new instance of EuclideanDistance.
- EUCLIDEANFUNCTION - Static variable in class org.ai_heuristic.util.AiHeuristicConst
-
- evalMetric - Variable in class org.ai_heuristic.algo.AlgorithmCompare
-
The metric to calculate the distance with.
- evalMetric - Variable in class org.ai_heuristic.algo.AlgorithmLearn
-
The metric to calculate the distance with
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.classify.InformationGain
-
Evaluate the resulting IG after splitting the datasets over each attribute (column variable),
apart from the decision attribute or column that the IG is being calculated for.
- evaluate(T) - Method in class org.ai_heuristic.algo.classify.Markov
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.classify.Markov
-
Evaluate the dataset and return the result.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.classify.VarGain
-
Evaluate a cohesive value, similar to an entropy value, for the combined variable
list and count.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.cluster.CompleteLinkCluster
-
Calculate the closest dataset from datasets to the parameter dataset.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.cluster.NearestNeighbour
-
Calculate the closest ksize data points from each pont to the other and use this to cluster.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.cluster.SingleLinkCluster
-
Calculate the closest dataset from the input list to the parameter dataset.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.algo.prob.Entropy
-
Evaluate the comparison of a list of values for the same element and return the result.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.algo.prob.KullbackLeibler
-
Evaluate the comparison of the two vectors of data and return the result.
- evaluate(double[], double[]) - Method in class org.ai_heuristic.algo.prob.KullbackLeibler
-
Evaluate the Kullback-Leibler divergence going from q to p.
- evaluate(Object) - Method in class org.ai_heuristic.algo.prob.NGram
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.algo.prob.NGram
-
Evaluate the comparison of the two vectors of data and return the result.
- evaluate(String, String) - Method in class org.ai_heuristic.algo.prob.NGram
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in interface org.ai_heuristic.def.FunctionDef
-
Evaluate the objects stored in the dataset.
- evaluate(MetricDataset, MetricDataset) - Method in interface org.ai_heuristic.def.FunctionMetricDef
-
Evaluate the comparison between the two datasets and return the result.
- evaluate(String, String, String) - Method in class org.ai_heuristic.eval.MathString
-
Evaluate the expression and return true if true.
- evaluate(Integer, Integer, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(Character, Character, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(Long, Long, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(Float, Float, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(Double, Double, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(String, String, String) - Method in class org.ai_heuristic.eval.SimpleMathCompare
-
Evaluate the expression and return true if true.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionHardLimit
-
Return a value based on the function evaluation.
- evaluate(double, double) - Method in class org.ai_heuristic.functs.activate.FunctionHardLimit
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionLinear
-
Return a value based on the function evaluation.
- evaluate(double) - Method in class org.ai_heuristic.functs.activate.FunctionLinear
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionLinearPlus
-
Return a value based on the function evaluation.
- evaluate(double, double, double) - Method in class org.ai_heuristic.functs.activate.FunctionLinearPlus
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionLinearRectified
-
Return a value based on the function evaluation.
- evaluate(double) - Method in class org.ai_heuristic.functs.activate.FunctionLinearRectified
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionSigmoid
-
Return a value based on the function evaluation.
- evaluate(double) - Method in class org.ai_heuristic.functs.activate.FunctionSigmoid
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionSymmetricHardLimit
-
Return a value based on the function evaluation.
- evaluate(double, double) - Method in class org.ai_heuristic.functs.activate.FunctionSymmetricHardLimit
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.activate.FunctionTanH
-
Return a value based on the function evaluation.
- evaluate(double) - Method in class org.ai_heuristic.functs.activate.FunctionTanH
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.Function
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.FunctionMetric
-
Evaluate the comparison between the two datasets and return the result.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.FunctionSingle
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.learn.FunctionConstantFactor
-
Return a value based on the function evaluation.
- evaluate(double) - Method in class org.ai_heuristic.functs.learn.FunctionConstantFactor
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.learn.FunctionCount
-
Return a value based on the function evaluation.
- evaluate(double, double) - Method in class org.ai_heuristic.functs.learn.FunctionCount
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.learn.FunctionExponentialFactor
-
Return a value based on the function evaluation.
- evaluate(double, double, double) - Method in class org.ai_heuristic.functs.learn.FunctionExponentialFactor
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.learn.FunctionGaussFactor
-
Return a value based on the function evaluation.
- evaluate(double, double) - Method in class org.ai_heuristic.functs.learn.FunctionGaussFactor
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.learn.FunctionHyperbolicFactor
-
Return a value based on the function evaluation.
- evaluate(double, double, double) - Method in class org.ai_heuristic.functs.learn.FunctionHyperbolicFactor
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.metric.CityBlockDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(double[], double[]) - Method in class org.ai_heuristic.functs.metric.CityBlockDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.metric.CosineSimilarity
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(double[], double[]) - Method in class org.ai_heuristic.functs.metric.CosineSimilarity
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.metric.EuclideanDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(double[], double[]) - Method in class org.ai_heuristic.functs.metric.EuclideanDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.metric.JaccardCoefficient
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String[], String[]) - Method in class org.ai_heuristic.functs.metric.JaccardCoefficient
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.metric.MinkowskiDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(double[], double[], int) - Method in class org.ai_heuristic.functs.metric.MinkowskiDistance
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(Object) - Method in class org.ai_heuristic.functs.similar.DemerauLevenshtein
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.similar.DemerauLevenshtein
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String, String) - Method in class org.ai_heuristic.functs.similar.DemerauLevenshtein
-
Return a value based on the function evaluation.
- evaluate(Object) - Method in class org.ai_heuristic.functs.similar.Hamming
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.similar.Hamming
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String, String) - Method in class org.ai_heuristic.functs.similar.Hamming
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.similar.IndexSimilarity
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String[], String[]) - Method in class org.ai_heuristic.functs.similar.IndexSimilarity
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(Object) - Method in class org.ai_heuristic.functs.similar.JaroWinkler
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.similar.JaroWinkler
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String, String) - Method in class org.ai_heuristic.functs.similar.JaroWinkler
-
Return a value based on the function evaluation.
- evaluate(Object) - Method in class org.ai_heuristic.functs.similar.Levenshtein
-
Return a value based on the function evaluation.
- evaluate(MetricDataset, MetricDataset) - Method in class org.ai_heuristic.functs.similar.Levenshtein
-
Evaluate the comparison between the two data lists and return the result.
- evaluate(String, String) - Method in class org.ai_heuristic.functs.similar.Levenshtein
-
Return a value based on the function evaluation.
- evaluate(MetricDataset) - Method in class org.ai_heuristic.functs.test.SimpleFunction
-
Return a value based on the function evaluation.
- EvaluateBase - Class in org.ai_heuristic.eval
-
Provides some base evaluation functions.
- EvaluateBase() - Constructor for class org.ai_heuristic.eval.EvaluateBase
-
Create a new instance of Evaluate.
- evaluateCompare(MetricCompare) - Method in class org.ai_heuristic.functs.FunctionMetric
-
Return a value based on the function evaluation.
- EvaluateMathDef - Interface in org.ai_heuristic.def
-
This defines the methods that should be implemented by an evaluator of mathematical
operations if they are typically comparisons or operations between two or more values.
- evaluateSingle(MetricDataset) - Method in class org.ai_heuristic.functs.FunctionSingle
-
Return a value based on the function evaluation.
- evaluator - Variable in class org.ai_heuristic.tree.KD_TreeNode
-
For comparing tree values.
- EVALUATOR - Static variable in class org.ai_heuristic.util.AiHeuristicConst
-
- exp(int) - Static method in class org.ai_heuristic.functs.MathStat
-
Calculate the value of e raised to the power of power.