Serialized Form


Package weka.classifiers.lazy

Class weka.classifiers.lazy.IBk extends AbstractClassifier implements Serializable

serialVersionUID: -3080186098777067172L

Serialized Fields

m_Train

Instances m_Train

m_NumClasses

int m_NumClasses

m_ClassType

int m_ClassType

m_kNN

int m_kNN

m_kNNUpper

int m_kNNUpper

m_kNNValid

boolean m_kNNValid

m_WindowSize

int m_WindowSize

m_DistanceWeighting

int m_DistanceWeighting

m_CrossValidate

boolean m_CrossValidate

m_MeanSquared

boolean m_MeanSquared

m_defaultModel

ZeroR m_defaultModel

m_NNSearch

NearestNeighbourSearch m_NNSearch

m_NumAttributesUsed

double m_NumAttributesUsed

Class weka.classifiers.lazy.KStar extends AbstractClassifier implements Serializable

serialVersionUID: 332458330800479083L

Serialized Fields

m_Train

Instances m_Train

m_NumInstances

int m_NumInstances

m_NumClasses

int m_NumClasses

m_NumAttributes

int m_NumAttributes

m_ClassType

int m_ClassType

m_RandClassCols

int[][] m_RandClassCols

m_ComputeRandomCols

int m_ComputeRandomCols

m_InitFlag

int m_InitFlag

m_Cache

KStarCache[] m_Cache

m_MissingMode

int m_MissingMode

m_BlendMethod

int m_BlendMethod

m_GlobalBlend

int m_GlobalBlend

Class weka.classifiers.lazy.LBR extends AbstractClassifier implements Serializable

serialVersionUID: 5648559277738985156L

Serialized Fields

m_Counts

int[][][] m_Counts
All the counts for nominal attributes.


m_tCounts

int[][][] m_tCounts
All the counts for nominal attributes.


m_Priors

int[] m_Priors
The prior probabilities of the classes.


m_tPriors

int[] m_tPriors
The prior probabilities of the classes.


m_numAtts

int m_numAtts
number of attributes for the dataset


m_numClasses

int m_numClasses
number of classes for dataset


m_numInsts

int m_numInsts
number of instances in dataset


m_Instances

Instances m_Instances
The set of instances used for current training.


m_Errors

int m_Errors
leave-one-out errors on the training dataset.


m_ErrorFlags

boolean[] m_ErrorFlags
leave-one-out error flags on the training dataaet.


leftHand

java.util.ArrayList<E> leftHand
best attribute's index list. maybe as output result


m_subOldErrorFlags

boolean[] m_subOldErrorFlags
following is defined by wangzh, the number of instances to be classified incorrectly on the subset.


m_RemainderErrors

int m_RemainderErrors
the number of instances to be classified incorrectly besides the subset.


m_Number

int m_Number
the number of instance to be processed


m_NumberOfInstances

int m_NumberOfInstances
the Number of Instances to be used in building a classifiers


m_NCV

boolean m_NCV
for printing in n-fold cross validation


m_subInstances

LBR.Indexes m_subInstances
index of instances and attributes for the given dataset


tempSubInstances

LBR.Indexes tempSubInstances
index of instances and attributes for the given dataset


posteriorsArray

double[] posteriorsArray
probability values array


bestCnt

int bestCnt

tempCnt

int tempCnt

forCnt

int forCnt

whileCnt

int whileCnt

Class weka.classifiers.lazy.LBR.Indexes extends java.lang.Object implements Serializable

serialVersionUID: -2771490019751421307L

Serialized Fields

m_InstIndexes

boolean[] m_InstIndexes
the array instance indexes


m_AttIndexes

boolean[] m_AttIndexes
the array attribute indexes


m_NumInstances

int m_NumInstances
the number of instances indexed


m_NumAtts

int m_NumAtts
the number of attributes indexed


m_SequentialInstIndexes

int[] m_SequentialInstIndexes
the array of instance indexes that are set to a either true or false


m_SequentialAttIndexes

int[] m_SequentialAttIndexes
an array of attribute indexes that are set to either true or false


m_SequentialInstanceIndex_valid

boolean m_SequentialInstanceIndex_valid
flag to check if sequential array must be rebuilt due to changes to the instance index


m_SequentialAttIndex_valid

boolean m_SequentialAttIndex_valid
flag to check if sequential array must be rebuilt due to changes to the attribute index


m_NumInstsSet

int m_NumInstsSet
the number of instances "in use" or set to a the original value (true or false)


m_NumAttsSet

int m_NumAttsSet
the number of attributes "in use" or set to a the original value (true or false)


m_NumSeqInstsSet

int m_NumSeqInstsSet
the number of sequential instances "in use" or set to a the original value (true or false)


m_NumSeqAttsSet

int m_NumSeqAttsSet
the number of sequential attributes "in use" or set to a the original value (true or false)


m_ClassIndex

int m_ClassIndex
the Class Index for the data set

Class weka.classifiers.lazy.LWL extends SingleClassifierEnhancer implements Serializable

serialVersionUID: 1979797405383665815L

Serialized Fields

m_Train

Instances m_Train

m_kNN

int m_kNN

m_WeightKernel

int m_WeightKernel

m_UseAllK

boolean m_UseAllK

m_NNSearch

NearestNeighbourSearch m_NNSearch

m_ZeroR

Classifier m_ZeroR