Data Mining

Functions

Apriori — Market Basket Analysis

Computes frequent itemsets apriori

Computes frequent itemsets using aggregation aggr_apriori

Prints an Imsls_f_apriori_itemsets data structure write_apriori_itemsets

Prints an Imsls_f_association_rule data structure write_association_rules

Frees memory allocated for an
Imsls_f_apriori_itemsets data structure free_apriori_itemsets

Frees memory allocated for an
Imsls_f_association_rules data structure free_association_rules

Decision Trees

Decision Trees – An Overview

Generates a decision tree for a single response variable
and two or more predictor variables decision_tree

Computes predicted values using a decision tree decision_tree_predict

Prints a decision tree decision_tree_print

Frees the memory associated with a decision tree decision_tree_free

Frees the memory associated with an array of
decision trees bagged_trees_free

Performs stochastic gradient boosting of decision trees gradient_boosting

Computes predicted values using a stochastic gradient boosting model gradient_boosting_predict

Frees the memory associated with a gradient boosting model gradient_boosting_model_free

Retrieves a gradient boosting model previously filed gradient_boosting_model_read

Writes a gradient boosting model to an ASCII file gradient_boosting_model_write

 

Genetic Algorithms

Genetic Algorithms – An Overview

Genetic Algorithm Data Structures

Creates a chromosome ga_chromosome

Copies one chromosome to another ga_copy_chromosome

Clones an existing chromosome ga_clone_chromosome

Creates an individual ga_individual

Copies the contents of one individual into
another individual ga_copy_individual

Clones an existing individual ga_clone_individual

Applies mutation to an individual ga_mutate

Decodes an individual’s chromosome into its phenotype ga_decode

Encodes an individual’s phenotype into its chromosome ga_encode

Frees memory allocated to an individual ga_free_individual

Creates a population from an array of individuals ga_population

Creates a population of randomly selected
individuals ga_random_population

Copies a population into an existing population ga_copy_population

Creates a copy of a population ga_clone_population

Add individuals to a population ga_grow_population

Creates a new population by merging two
populations ga_merge_population

Frees memory allocated to a population ga_free_population

Genetic Algorithm Search and Optimization

Applies a genetic algorithm to find individuals with
maximum fitness genetic_algorithm

Naive Bayes

Naive Bayes – An Overview

Trains a Naive Bayes classifier naive_bayes_trainer

Classifies patterns using a previously trained
Naive Bayes classifier naive_bayes_classification

Frees memory allocated for a Naive Bayes
classifier nb_classifier_free

Writes a Naive Bayes classifier to an ASCII file nb_classifier_write

Retrieves a Naive Bayes classifier nb_classifier_read

Neural Networks

Neural Networks – An Overview

Neural Network ^Data Structures

Multilayer Feedforward Neural Networks

Initializes a data structure for training
a neural network mlff_network_init

Multilayered feedforward neural network mlff_network

Frees memory allocated for an
Imsls_f_NN_Network data structure mlff_network_free

Writes a trained neural network to an
ASCII file mlff_network_write

Retrieves a neural network from a file
previously saved mlff_network_read

Initializes weights for neural network mlff_initialize_weights

Forecasting Neural Networks

Trains a multilayered feedforward
neural network mlff_network_trainer

Calculates forecasts for trained multilayered
feedforward neural networks mlff_network_forecast

Classification Neural Networks

Trains a neural network for classification mlff_classification_trainer

Calculates classifications from a
trained neural network mlff_pattern_classification

Preprocessing Data Filters

Encodes or decodes continuous input attributes scale_filter

Encodes a time series into lagged values time_series_filter

Encodes a time series into lagged values of
a nominal classification attribute time_series_class_filter

Encodes or decodes a nominal input
attributes unsupervised_nominal_filter

Encodes or decodes ordinal input
attributes unsupervised_ordinal_filter

Self-Organizing Maps

Trains a Kohonen network kohonenSOM_trainer

Calculates forecasts using a trained Kohonen network kohonenSOM_forecast

Support Vector Machines

Support Vector Machines – An Overview

Trains a Support Vector Machines classifier support_vector_trainer

Classifies patterns using a previously trained
Support Vector Machines classifier support_vector_classification

Frees memory allocated for a Support Vector Machines
classifier svm_classifier_free

Utilities

Calculates Area Under the Curve for classification problems multiclass_auc