Serialized Form

Package codebook_generation

Class codebook_generation.SimpleKMeansWithOutput extends weka.clusterers.RandomizableClusterer implements Serializable

serialVersionUID: -3235809600124455376L

Serialized Fields

m_ReplaceMissingFilter

weka.filters.unsupervised.attribute.ReplaceMissingValues m_ReplaceMissingFilter

replace missing values in training instances.

m_NumClusters

int m_NumClusters

number of clusters to generate.

m_ClusterCentroids

weka.core.Instances m_ClusterCentroids

holds the cluster centroids.

m_ClusterStdDevs

weka.core.Instances m_ClusterStdDevs

Holds the standard deviations of the numeric attributes in each cluster.

m_ClusterNominalCounts

int[][][] m_ClusterNominalCounts

For each cluster, holds the frequency counts for the values of each nominal attribute.

m_ClusterMissingCounts

int[][] m_ClusterMissingCounts

m_FullMeansOrMediansOrModes

double[] m_FullMeansOrMediansOrModes

Stats on the full data set for comparison purposes. In case the attribute is numeric the value is the mean if is being used the Euclidian distance or the median if Manhattan distance and if the attribute is nominal then it's mode is saved.

m_FullStdDevs

double[] m_FullStdDevs

m_FullNominalCounts

int[][] m_FullNominalCounts

m_FullMissingCounts

int[] m_FullMissingCounts

m_displayStdDevs

boolean m_displayStdDevs

Display standard deviations for numeric atts.

m_dontReplaceMissing

boolean m_dontReplaceMissing

Replace missing values globally?

m_ClusterSizes

int[] m_ClusterSizes

The number of instances in each cluster.

m_MaxIterations

int m_MaxIterations

Maximum number of iterations to be executed.

m_Iterations

int m_Iterations

Keep track of the number of iterations completed before convergence.

m_squaredErrors

double[] m_squaredErrors

Holds the squared errors for all clusters.

m_DistanceFunction

weka.core.DistanceFunction m_DistanceFunction

the distance function used.

m_PreserveOrder

boolean m_PreserveOrder

Preserve order of instances.

m_Assignments

int[] m_Assignments

Assignments obtained.

m_FastDistanceCalc

boolean m_FastDistanceCalc

whether to use fast calculation of distances (using a cut-off).

m_initializeWithKMeansPlusPlus

boolean m_initializeWithKMeansPlusPlus

Whether to initialize cluster centers using the k-means++ method

m_executionSlots

int m_executionSlots

m_completed

int m_completed

m_failed

int m_failed