Data Mining¶
Functions¶
Apriori — Market Basket Analysis¶
Computes frequent itemsets apriori
Computes frequent itemsets using aggregation aggrApriori
Prints an structure data structure writeAprioriItemsets
Prints an Imsls_f_association_rule data structure writeAssociationRules
Frees memory allocated for an
structure data structure freeAprioriItemsets
Frees memory allocated for an
Imsls_f_association_rules data structure freeAssociationRules
Decision Trees¶
Generates a decision tree for a single response variable
and two or more predictor variables decisionTree
Computes predicted values using a decision tree decisionTreePredict
Prints a decision tree decisionTreePrint
Frees the memory associated with a decision tree decisionTreeFree
Genetic Algorithms¶
Genetic Algorithms – An Overview
Genetic Algorithm Data Structures
Creates a chromosome gaChromosome
Copies one chromosome to another gaCopyChromosome
Clones an existing chromosome gaCloneChromosome
Creates an individual gaIndividual
Copies the contents of one individual into
another individual gaCopyIndividual
Clones an existing individual gaCloneIndividual
Applies mutation to an individual gaMutate
Decodes an individual’s chromosome into its phenotype gaDecode
Encodes an individual’s phenotype into its chromosome gaEncode
Frees memory allocated to an individual gaFreeIndividual
Creates a population from an array of individuals gaPopulation
Creates a population of randomly selected
individuals gaRandomPopulation
Copies a population into an existing population gaCopyPopulation
Creates a copy of a population gaClonePopulation
Add individuals to a population gaGrowPopulation
Creates a new population by merging two
populations gaMergePopulation
Frees memory allocated to a population gaFreePopulation
Genetic Algorithm Search and Optimization
Applies a genetic algorithm to find individuals with
maximum fitness geneticAlgorithm
Naive Bayes¶
Trains a Naive Bayes classifier naiveBayesTrainer
Classifies patterns using a previously trained
Naive Bayes classifier naiveBayesClassification
Frees memory allocated for a Naive Bayes
classifier nbClassifierFree
Writes a Naive Bayes classifier to an ASCII file nbClassifierWrite
Retrieves a Naive Bayes classifier nbClassifierRead
Neural Networks¶
Neural Network Data Structures
Multilayer Feedforward Neural Networks
Initializes a data structure for training
a neural network mlffNetworkInit
Multilayered feedforward neural network mlffNetwork
Frees memory allocated for an
Imsls_d_NN_Network data structure mlffNetworkFree
Writes a trained neural network to an
ASCII file mlffNetworkWrite
Retrieves a neural network from a file
previously saved mlffNetworkRead
Initializes weights for neural network mlffInitializeWeights
Forecasting Neural Networks
Trains a multilayered feedforward
neural network mlffNetworkTrainer
Calculates forecasts for trained multilayered
feedforward neural networks mlffNetworkForecast
Classification Neural Networks
Trains a neural network for classification mlffClassificationTrainer
Calculates classifications from a
trained neural network mlffPatternClassification
Preprocessing Data Filters¶
Encodes or decodes continuous input attributes scaleFilter
Encodes a time series into lagged values timeSeriesFilter
Encodes a time series into lagged values of
a nominal classification attribute timeSeriesClassFilter
Encodes or decodes a nominal input
attributes unsupervisedNominalFilter
Encodes or decodes ordinal input
attributes unsupervisedOrdinalFilter
Self-Organizing Maps¶
Trains a Kohonen network kohonenSOMTrainer
Calculates forecasts using a trained Kohonen network kohonenSOMForecast
Support Vector Machines¶
Support Vector Machines – An Overview
Trains a Support Vector Machines classifier supportVectorTrainer
Classifies patterns using a previously trained
Support Vector Machines classifier supportVectorClassification
Frees memory allocated for a Support Vector Machines
classifier svmClassifierFree