Python* API Reference for Intel® Data Analytics Acceleration Library 2020 Update 1

Public Member Functions | Static Public Attributes | List of all members
interface2_Parameter Class Reference

AdaBoost algorithm parameters. More...

Public Member Functions

def __init__
 
def check
 
- Public Member Functions inherited from interface2_Parameter
def __init__
 
def check
 
- Public Member Functions inherited from Parameter
def __init__
 
def check
 

Static Public Attributes

 weakLearnerTraining = ...
 
 weakLearnerPrediction = ...
 
 accuracyThreshold = ...
 
 maxIterations = ...
 
 learningRate = ...
 
 resultsToCompute = ...
 
- Static Public Attributes inherited from interface2_Parameter
 nClasses = ...
 
 resultsToEvaluate = ...
 

Detailed Description

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1

Default contructor

Parameters
nClassesThe number of classes

Variant 2

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Variant 3

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Variant 4

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Variant 5

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Variant 6

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Variant 7

Constructs the AdaBoost parameter structure

Parameters
wlTrainForParameterPointer to the training algorithm of the weak learner
wlPredictForParameterPointer to the prediction algorithm of the weak learner
accAccuracy of the AdaBoost training algorithm
maxIterMaximal number of iterations of the AdaBoost training algorithm
learnRateMultiplier for each classifier to shrink its contribution
resToComputeThe 64-bit integer flag that specifies which extra characteristics of the AdaBoost compute from ResultToComputeId
nClNumber of classes

Member Function Documentation

def check (   self)

check(interface2_Parameter self) -> Status

Member Data Documentation

accuracyThreshold = ...
static

Accuracy of the AdaBoost training algorithm

learningRate = ...
static

Multiplier for each classifier to shrink its contribution

maxIterations = ...
static

Maximal number of iterations of the AdaBoost training algorithm

resultsToCompute = ...
static

64 bit integer flag that indicates the results to compute

weakLearnerPrediction = ...
static

The algorithm for prediction based on a weak learner model

weakLearnerTraining = ...
static

The algorithm for weak learner model training


The documentation for this class was generated from the following file:

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