Package hhreco.classification

This package provides data structures such as feature sets, training sets, as well as a classification framework for facilitating pattern classification tasks.

See:
          Description

Interface Summary
Classifier A Classifier performs generic classification on feature sets, the semantics of which it knows nothing about.
TrainableClassifier This classifier trains on a data set and performs classification based on what it has seen.
 

Class Summary
Classification Data structure for storing a list of classifer type and confidence value pairs in the order of descending confidence values.
DataRep Representing a collection of data with the means, standard deviations, and variances of the feature components.
FeatureSet A data structure for storing features of an example; it is basically a typesafe array of doubles with appropriate accessor methods.
KNNClassifier This K-nearest neighbor classifier compares a test example with every example in the training set by computing the normalized Euclidean distance.
MMDClassifier Minimum distance classifier measures the normalized Euclidean distance between the test example and each of the training classes.
SVMClassifier This class uses libsvm, a SVM software library written in Java, to do SVM classification.
TrainingSet A TrainingSet contains a set of types, and for each type a corresponding set of positive and negative examples.
 

Exception Summary
ClassifierException Thrown when there is some internal error in the training or classification process.
 

Package hhreco.classification Description

This package provides data structures such as feature sets, training sets, as well as a classification framework for facilitating pattern classification tasks. It also includes 3 classifier implementations: SVM, minimum mean distance classifier, and nearest neighbor.