Serialized Form (Trainable Segmentation 4.0.0 API)

Package ai
- Class ai.BalancedRandomForest extends weka.classifiers.AbstractClassifier implements Serializable
  - Serialized Fields
    - seed
```
int seed
```
      random seed
    - numTrees
```
int numTrees
```
      number of trees
    - numFeatures
```
int numFeatures
```
      number of features used on each node of the trees
    - tree
```
BalancedRandomTree[] tree
```
      array of random trees that form the forest
    - outOfBagError
```
double outOfBagError
```
      the out of bag error which has been calculated
- Class ai.BalancedRandomTree extends Object implements Serializable
  
  serialVersionUID:
  
  41518309467L
  - Serialized Fields
    - rootNode
```
ai.BalancedRandomTree.BaseNode rootNode
```
      root node
- Class ai.GiniFunction extends SplitFunction implements Serializable
  
  serialVersionUID:
  
  9707184791345L
  - Serialized Fields
    - index
```
int index
```
      index of the splitting attribute
    - threshold
```
double threshold
```
      threshold value of the splitting point
    - allSame
```
boolean allSame
```
      flag to identify when all samples belong to the same class
    - numOfFeatures
```
int numOfFeatures
```
      number of random features to use
    - random
```
Random random
```
      random number generator
- Class ai.InformationGainFunction extends SplitFunction implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - numOfFeatures
```
int numOfFeatures
```
      number of random features to use
    - random
```
Random random
```
      random number generator
- Class ai.SplitFunction extends Object implements Serializable
  
  serialVersionUID:
  
  1L
  - Serialized Fields
    - index
```
int index
```
    - threshold
```
double threshold
```
    - allSame
```
boolean allSame
```
- Class ai.Splitter extends Object implements Serializable
  
  serialVersionUID:
  
  52652189902462L
  - Serialized Fields
    - template
```
SplitFunction template
```
      split function template
Package hr.irb.fastRandomForest
- Class hr.irb.fastRandomForest.FastRandomForest extends weka.classifiers.AbstractClassifier implements Serializable
  
  serialVersionUID:
  
  4216839470751428700L
  - Serialized Fields
    - m_numTrees
```
int m_numTrees
```
      Number of trees in forest.
    - m_numFeatures
```
int m_numFeatures
```
      Number of features to consider in random feature selection. If less than 1 will use int(logM+1) )
    - m_randomSeed
```
int m_randomSeed
```
      The random seed.
    - m_KValue
```
int m_KValue
```
      Final number of features that were considered in last build.
    - m_NumThreads
```
int m_NumThreads
```
      Number of simultaneous threads to use in computation (0 = autodetect).
    - m_bagger
```
hr.irb.fastRandomForest.FastRfBagging m_bagger
```
      The bagger.
    - m_MaxDepth
```
int m_MaxDepth
```
      The maximum depth of the trees (0 = unlimited)
    - m_Info
```
weka.core.Instances m_Info
```
      The header information.
    - m_ZeroR
```
weka.classifiers.AbstractClassifier m_ZeroR
```
      a ZeroR model in case no model can be built from the data
    - m_FeatureImportances
```
double[] m_FeatureImportances
```
      The value of the features importances.
    - m_computeImportances
```
boolean m_computeImportances
```
      Whether to compute the importances or not.
- Class hr.irb.fastRandomForest.FRFAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable
  
  serialVersionUID:
  
  -4504270948574160991L
  - Serialized Fields
    - m_Importances
```
double[] m_Importances
```
      The feature importances.
    - m_frfProto
```
FastRandomForest m_frfProto
```
      The prototype for the rf.
Package trainableSegmentation
- Class trainableSegmentation.ReusableDenseInstance extends weka.core.DenseInstance implements Serializable
  
  serialVersionUID:
  
  -2322621365960366756L

Serialized Form

Package ai

Class ai.BalancedRandomForest extends weka.classifiers.AbstractClassifier implements Serializable

Serialized Fields

seed

numTrees

numFeatures

tree

outOfBagError

Class ai.BalancedRandomTree extends Object implements Serializable

Serialized Fields

rootNode

Class ai.GiniFunction extends SplitFunction implements Serializable

Serialized Fields

index

threshold

allSame

numOfFeatures

random

Class ai.InformationGainFunction extends SplitFunction implements Serializable

Serialized Fields

numOfFeatures

random

Class ai.SplitFunction extends Object implements Serializable

Serialized Fields

index

threshold

allSame

Class ai.Splitter extends Object implements Serializable

Serialized Fields

template

Package hr.irb.fastRandomForest

Class hr.irb.fastRandomForest.FastRandomForest extends weka.classifiers.AbstractClassifier implements Serializable

Serialized Fields

m_numTrees

m_numFeatures

m_randomSeed

m_KValue

m_NumThreads

m_bagger

m_MaxDepth

m_Info

m_ZeroR

m_FeatureImportances

m_computeImportances

Class hr.irb.fastRandomForest.FRFAttributeEval extends weka.attributeSelection.ASEvaluation implements Serializable

Serialized Fields

m_Importances

m_frfProto

Package trainableSegmentation

Class trainableSegmentation.ReusableDenseInstance extends weka.core.DenseInstance implements Serializable