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

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

Provides methods to run implementations of the KD-tree based kNN model-based prediction. More...

Public Member Functions

def __init__
 
def getInput
 
def getMethod
 
def clone
 
def compute
 
- Public Member Functions inherited from Batch
def getInput
 
def getResult
 
def setResult
 
def clone
 
def compute
 
- Public Member Functions inherited from AlgorithmImpl
def computeNoThrow
 
def compute
 
def checkComputeParams
 
def checkResult
 
def setupCompute
 
def resetCompute
 
def enableResetOnCompute
 
def hostApp
 
def setHostApp
 
- Public Member Functions inherited from Algorithm
def checkComputeParams
 
def getBaseParameter
 
- Public Member Functions inherited from AlgorithmIfaceImpl
def enableChecks
 
def isChecksEnabled
 
- Public Member Functions inherited from AlgorithmIface
def checkComputeParams
 
def checkResult
 
def getMethod
 

Static Public Attributes

 input = ...
 
 parameter = ...
 

Detailed Description

Parameters
fptypeData type to use in intermediate computations for KD-tree based kNN model-based prediction in the batch processing mode, double or float
methodComputation method in the batch processing mode, Method
Enumerations
  • Method Computation methods for KD-tree based kNN model-based prediction
References
Aliases
  • Batch_Float64DefaultDense is an alias of Batch(fptype=float64, method=daal.algorithms.kdtree_knn_classification.prediction.defaultDense)
  • Batch_Float32DefaultDense is an alias of Batch(fptype=float32, method=daal.algorithms.kdtree_knn_classification.prediction.defaultDense)

Constructor & Destructor Documentation

def __init__ (   self,
  args 
)

Variant 1
Default constructor

Variant 2

Constructs a KD-tree based kNN prediction algorithm by copying input objects and parameters of another KD-tree based kNN prediction algorithm

Parameters
otherAlgorithm to use as the source to initialize the input objects and parameters of the algorithm

Member Function Documentation

def clone (   self)

Returns a pointer to the newly allocated KD-tree based kNN prediction algorithm with a copy of input objects of this KD-tree based kNN prediction algorithm

Returns
Pointer to the newly allocated algorithm
def compute (   self)

Invokes computations

def getInput (   self)

Get input objects for the KD-tree based kNN prediction algorithm

Returns
Input objects for the KD-tree based kNN prediction algorithm
def getMethod (   self)

Returns the method of the algorithm

Returns
Method of the algorithm

Member Data Documentation

input = ...
static

Input data structure

parameter = ...
static

Parameters of prediction


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

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