Enumerator |
---|
ErrorMethodNotSupported |
Method not supported by the algorithm
|
ErrorIncorrectNumberOfFeatures |
Number of columns in numeric table is incorrect
|
ErrorIncorrectNumberOfObservations |
Number of rows in numeric table is incorrect
|
ErrorIncorrectSizeOfArray |
Incorrect size of array
|
ErrorNullParameterNotSupported |
Null parameter is not supported by the algorithm
|
ErrorIncorrectNumberOfArguments |
Number of arguments is incorrect
|
ErrorIncorrectInputNumericTable |
Input numeric table is incorrect
|
ErrorEmptyInputNumericTable |
Input numeric table is empty
|
ErrorIncorrectDataRange |
Data range is incorrect
|
ErrorPrecomputedStatisticsIndexOutOfRange |
Precomputed statistics index is out of range
|
ErrorIncorrectNumberOfInputNumericTables |
Incorrect number of input numeric tables
|
ErrorIncorrectNumberOfOutputNumericTables |
Incorrect number of output numeric tables
|
ErrorNullInputNumericTable |
Null input numeric table is not supported
|
ErrorNullOutputNumericTable |
Null output numeric table is not supported
|
ErrorNullModel |
Null model is not supported
|
ErrorInconsistentNumberOfRows |
Number of rows in provided numeric tables is inconsistent
|
ErrorIncorrectSizeOfInputNumericTable |
Number of columns or rows in input numeric table is incorrect
|
ErrorIncorrectSizeOfOutputNumericTable |
Number of columns or rows in output numeric table is incorrect
|
ErrorIncorrectNumberOfRowsInInputNumericTable |
Number of rows in input numeric table is incorrect
|
ErrorIncorrectNumberOfColumnsInInputNumericTable |
Number of columns in input numeric table is incorrect
|
ErrorIncorrectNumberOfRowsInOutputNumericTable |
Number of rows in output numeric table is incorrect
|
ErrorIncorrectNumberOfColumnsInOutputNumericTable |
Number of columns in output numeric table is incorrect
|
ErrorIncorrectTypeOfInputNumericTable |
Incorrect type of input NumericTable
|
ErrorIncorrectTypeOfOutputNumericTable |
Incorrect type of output NumericTable
|
ErrorIncorrectNumberOfElementsInInputCollection |
Incorrect number of elements in input collection
|
ErrorIncorrectNumberOfElementsInResultCollection |
Incorrect number of elements in result collection
|
ErrorNullInput |
Input not set
|
ErrorNullResult |
Result not set
|
ErrorIncorrectParameter |
Incorrect parameter
|
ErrorModelNotFullInitialized |
Model is not full initialized
|
ErrorInconsistentNumberOfColumns |
Inconsistent number of rows in Numeric Table
|
ErrorIncorrectIndex |
Index in collection is out of range
|
ErrorDataArchiveInternal |
Incorrect size of data block
|
ErrorNullPartialModel |
Null partial model is not supported
|
ErrorNullInputDataCollection |
Null input data collection is not supported
|
ErrorNullOutputDataCollection |
Null output data collection is not supported
|
ErrorNullPartialResult |
Partial result not set
|
ErrorIncorrectNumberOfInputNumericTensors |
Incorrect number of elements in input collection
|
ErrorIncorrectNumberOfOutputNumericTensors |
Incorrect number of elements in output collection
|
ErrorNullTensor |
Null tensor is not supported
|
ErrorIncorrectNumberOfDimensionsInTensor |
Number of dimensions in tensor is incorrect
|
ErrorIncorrectSizeOfDimensionInTensor |
Size of the dimension in input tensor is incorrect
|
ErrorNullLayerData |
Null layer data is not supported
|
ErrorIncorrectSizeOfLayerData |
Incorrect number of elements in layer data collection
|
ErrorNullNumericTable |
Null numeric table is not supported
|
ErrorIncorrectNumberOfColumns |
Number of columns in numeric table is incorrect
|
ErrorIncorrectNumberOfRows |
Number of rows in numeric table is incorrect
|
ErrorIncorrectTypeOfNumericTable |
Incorrect type of Numeric Table
|
ErrorUnsupportedCSRIndexing |
CSR Numeric Table has unsupported indexing type
|
ErrorSignificanceLevel |
Incorrect significance level value
|
ErrorAccuracyThreshold |
Incorrect accuracy threshold
|
ErrorIncorrectNumberOfBetas |
Incorrect number of betas in linear regression model
|
ErrorIncorrectNumberOfBetasInReducedModel |
Incorrect number of betas in reduced linear regression model
|
ErrorNumericTableIsNotSquare |
Numeric table is not square
|
ErrorNullAuxiliaryAlgorithm |
Null auxiliary algorithm
|
ErrorNullInitializationProcedure |
Null initialization procedure
|
ErrorNullAuxiliaryDataCollection |
Null auxiliary data collection
|
ErrorEmptyAuxiliaryDataCollection |
Empty auxiliary data collection
|
ErrorIncorrectElementInCollection |
Incorrect element in collection
|
ErrorNullPartialResultDataCollection |
Null partial result data collection
|
ErrorIncorrectElementInPartialResultCollection |
Incorrect element in collection of partial results
|
ErrorIncorrectElementInNumericTableCollection |
Incorrect element in collection of numeric tables
|
ErrorNullOptionalResult |
Null optional result
|
ErrorIncorrectOptionalResult |
Incorrect optional result
|
ErrorIncorrectOptionalInput |
Incorrect optional input
|
ErrorIncorrectNumberOfPartialClusters |
Incorrect number of partial clusters
|
ErrorIncorrectTotalNumberOfPartialClusters |
Incorrect total number of partial clusters
|
ErrorIncorrectDataCollectionSize |
Incorrect DataCollection size
|
ErrorIncorrectValueInTheNumericTable |
Incorrect value in the numeric table
|
ErrorIncorrectItemInDataCollection |
Incorrect item in data collection
|
ErrorNullPtr |
Null pointer in input arguments
|
ErrorUndefinedFeature |
Dictionary contains a undefined feature
|
ErrorCloneMethodFailed |
Cloning of algorithm failed
|
ErrorDataTypeNotSupported |
Data type not supported
|
ErrorBufferSizeIntegerOverflow |
Integer oveflow is occured during buffer size calculation
|
ErrorCpuIsInvalid |
Invalid CPU value used
|
ErrorCpuNotSupported |
CPU not supported
|
ErrorMemoryAllocationFailed |
Memory allocation failed
|
ErrorEmptyDataBlock |
Empty data block
|
ErrorMemoryCopyFailedInternal |
Memory copy internal error
|
ErrorIncorrectCombinationOfComputationModeAndStep |
Incorrect combination of computation mode and computation step
|
ErrorDictionaryAlreadyAvailable |
Data Dictionary is already available
|
ErrorDictionaryNotAvailable |
Data Dictionary is not available
|
ErrorNumericTableNotAvailable |
Numeric Table is not available
|
ErrorNumericTableAlreadyAllocated |
Numeric Table was already allocated
|
ErrorNumericTableNotAllocated |
Numeric Table is not allocated
|
ErrorPrecomputedSumNotAvailable |
Precomputed sums are not available
|
ErrorPrecomputedMinNotAvailable |
Precomputed minimum values are not available
|
ErrorPrecomputedMaxNotAvailable |
Precomputed maximum values are not available
|
ErrorServiceMicroTableInternal |
Numeric Table internal error
|
ErrorEmptyCSRNumericTable |
CSR Numeric Table is empty
|
ErrorEmptyHomogenNumericTable |
Homogeneous Numeric Table is empty
|
ErrorSourceDataNotAvailable |
Source data is not available
|
ErrorEmptyDataSource |
Data source is empty
|
ErrorIncorrectClassLabels |
Class labels provided to classification algorithm are incorrect
|
ErrorIncorrectSizeOfModel |
Incorrect size of model
|
ErrorIncorrectTypeOfModel |
Incorrect type of model
|
ErrorIncorrectErrorcodeFromGenerator |
Incorrect error code is returned from data generator
|
ErrorLeapfrogUnsupported |
Leapfrog method is not supported by generator
|
ErrorSkipAheadUnsupported |
SkipAhead method is not supported by generator
|
ErrorFeatureNamesNotAvailable |
Feature names are not available for feature modifier
|
ErrorInputSigmaMatrixHasNonPositiveMinor |
Input sigma matrix has non positive minor
|
ErrorInputSigmaMatrixHasIllegalValue |
Input sigma matrix has illegal value
|
ErrorIncorrectInternalFunctionParameter |
Incorrect parameter in internal function call
|
ErrorUserCancelled |
Computation cancelled at user's request
|
ErrorAprioriIncorrectItemsetTableSize |
Number of rows in the output table containing 'large' item sets is too small
|
ErrorAprioriIncorrectSupportTableSize |
Number of rows in the output table containing 'large' item sets support values is too small
|
ErrorAprioriIncorrectLeftRuleTableSize |
Number of rows in the output table containing left parts of the association rules is too small
|
ErrorAprioriIncorrectRightRuleTableSize |
Number of rows in the output table containing right parts of the association rules is too small
|
ErrorAprioriIncorrectConfidenceTableSize |
Number of rows in the output table containing association rules confidence is too small
|
ErrorAprioriIncorrectInputData |
Incorrect input data
|
ErrorInconsistentNumberOfClasses |
Inconsistent number of classes between boosting algorithm and weak learner
|
ErrorCholeskyInternal |
Cholesky internal error
|
ErrorInputMatrixHasNonPositiveMinor |
Input matrix has non positive minor
|
ErrorCovarianceInternal |
Covariance internal error
|
ErrorEMMatrixInverse |
Sigma matrix on M-step cannot be inverted
|
ErrorEMIncorrectToleranceToConverge |
Incorrect value of tolerance to converge in EM parameter
|
ErrorEMIllConditionedCovarianceMatrix |
Ill-conditioned covariance matrix
|
ErrorEMIncorrectMaxNumberOfIterations |
Incorrect maximum number of iterations value in EM parameter
|
ErrorEMNegativeDefinedCovarianceMartix |
Negative-defined covariance matrix
|
ErrorEMEmptyComponent |
Empty component during computation
|
ErrorEMCovariance |
Error during covariance computation for component on M step
|
ErrorEMIncorrectNumberOfComponents |
Incorrect number of components value in EM parameter
|
ErrorEMInitNoTrialConverges |
No trial of internal EM start converges
|
ErrorEMInitIncorrectToleranceToConverge |
Incorrect tolerance to converge value in EM initialization parameter
|
ErrorEMInitIncorrectDepthNumberIterations |
Incorrect depth number of iterations value in EM init parameter
|
ErrorEMInitIncorrectNumberOfTrials |
Incorrect number of trials value in EM initialization parameter
|
ErrorEMInitIncorrectNumberOfComponents |
Incorrect numeber of components value in EM initialization parameter
|
ErrorEMInitInconsistentNumberOfComponents |
Inconsistent number of component: number of observations should be greater than number of components
|
ErrorVarianceComputation |
Error during variance computation
|
ErrorKMeansNumberOfClustersIsTooLarge |
Number of clusters exceeds the number of points
|
ErrorLinearRegressionInternal |
Linear Regression internal error
|
ErrorNormEqSystemSolutionFailed |
Failed to solve the system of normal equations
|
ErrorLinRegXtXInvFailed |
Failed to invert Xt*X matrix
|
ErrorLowOrderMomentsInternal |
Low Order Moments internal error
|
ErrorIncorrectNumberOfClasses |
Number of classes provided to classifier is too small
|
ErrorMultiClassNullTwoClassTraining |
Null two-class classifier training algorithm is not supported
|
ErrorMultiClassFailedToTrainTwoClassClassifier |
Failed to train a model of two-class classifier
|
ErrorMultiClassFailedToComputeTwoClassPrediction |
Failed to compute prediction based on two-class classifier model
|
ErrorEmptyInputCollection |
Naive Bayes: Input collection is empty
|
ErrorNaiveBayesIncorrectModel |
Naive Bayes: Input model is not consistent with the number of classes
|
ErrorOutlierDetectionInternal |
Outlier Detection internal error
|
ErrorPCAFailedToComputeCorrelationEigenvalues |
Failed to compute eigenvalues of the correlation matrix
|
ErrorPCACorrelationInputDataTypeSupportsOfflineModeOnly |
This type of the input data supports only offline mode of the computations
|
ErrorIncorrectCrossProductTableSize |
Number of columns or rows in cross-product numeric table is incorrect
|
ErrorCrossProductTableIsNotSquare |
Number of columns or rows in cross-product numeric table is not equal
|
ErrorInputCorrelationNotSupportedInOnlineAndDistributed |
Input correlation matrix is not supported in online and distributed computation modes
|
ErrorIncorrectNComponents |
Incorrect nComponents parameter: nComponents should be less or equal to number of columns in testing dataset
|
ErrorQRInternal |
QR internal error
|
ErrorQrIthParamIllegalValue |
QR internal error
|
ErrorQrXBDSQRDidNotConverge |
QR internal error
|
ErrorStumpIncorrectSplitFeature |
Incorrect split feature
|
ErrorStumpInvalidInputCategoricalData |
Invalid stump training data: all features in the input table are categorical and each feature has < 2 categories
|
ErrorSvdIthParamIllegalValue |
SVD internal error
|
ErrorSvdXBDSQRDidNotConverge |
SVD internal error
|
ErrorLCNinnerConvolution |
Error in convolution 2d layer
|
ErrorSVMPredictKernerFunctionCall |
SVM predict: error in kernel function call. Details are as follows.
|
ErrorIncorrectWeakLearnerClassificationAlgorithm |
Weak learner can not be casted to classifier algorithm
|
ErrorIncorrectWeakLearnerRegressionAlgorithm |
Weak learner can not be casted to regression algorithm
|
ErrorIncorrectWeakLearnerClassificationModel |
Weak learner's model can not be casted to classifier model
|
ErrorIncorrectWeakLearnerRegressionModel |
Weak learner's model can not be casted to regression model
|
ErrorCompressionNullInputStream |
Null input stream is not supported
|
ErrorCompressionNullOutputStream |
Null output stream is not supported
|
ErrorCompressionEmptyInputStream |
Input stream of size 0 is not supported
|
ErrorCompressionEmptyOutputStream |
Output stream of size 0 is not supported
|
ErrorZlibInternal |
Zlib internal error
|
ErrorZlibDataFormat |
Input compressed stream is in wrong format, corrupted or contains not a whole number of compressed blocks
|
ErrorZlibParameters |
Unsupported Zlib parameters
|
ErrorZlibMemoryAllocationFailed |
Internal Zlib memory allocation failed
|
ErrorZlibNeedDictionary |
Specific dictionary is needed for decompression, currently unsupported Zlib feature
|
ErrorBzip2Internal |
Bzip2 internal error
|
ErrorBzip2DataFormat |
Input compressed stream is in wrong format, corrupted or contains not a whole number of compressed blocks
|
ErrorBzip2Parameters |
Unsupported Bzip2 parameters
|
ErrorBzip2MemoryAllocationFailed |
Internal Bzip2 memory allocation failed
|
ErrorLzoInternal |
LZO internal error
|
ErrorLzoOutputStreamSizeIsNotEnough |
Size of output stream is not enough to start compression
|
ErrorLzoDataFormat |
Input compressed stream is in wrong format or corrupted
|
ErrorLzoDataFormatLessThenHeader |
Size of input compressed stream is less then compressed block header size
|
ErrorLzoDataFormatNotFullBlock |
Input compressed stream contains not a whole number of compressed blocks
|
ErrorRleInternal |
RLE internal error
|
ErrorRleOutputStreamSizeIsNotEnough |
Size of output stream is not enough to start compression
|
ErrorRleDataFormat |
Input compressed stream is in wrong format or corrupted
|
ErrorRleDataFormatLessThenHeader |
Size of input compressed stream is less then compressed block header size
|
ErrorRleDataFormatNotFullBlock |
Input compressed stream contains not a whole number of compressed blocks
|
ErrorLowerBoundGreaterThanOrEqualToUpperBound |
Lower bound parameter greater than or equal to upper bound
|
ErrorQuantileOrderValueIsInvalid |
Quantile order value is invalid
|
ErrorQuantilesInternal |
Quantile internal error
|
ErrorALSInternal |
ALS algorithm failed to solve a system of normal equations
|
ErrorALSInconsistentSparseDataBlocks |
Failed to find a non-zero value with needed indices in a sparse data block
|
ErrorSorting |
Cannot sort the numeric table
|
ErrorNegativeLearningRate |
Negative learning rate
|
ErrorMeanAndStandardDeviationComputing |
Computation of mean and standard deviation failed
|
ErrorNullVariance |
Failed to normalize data in column: it has null variance deviation
|
ErrorMinAndMaxComputing |
Computation of minimum and maximum failed
|
ErrorZeroNumberOfTerms |
Number of terms can not be zero
|
ErrorConvolutionInternal |
Convoltion internal error
|
ErrorIncorrectKernelSise1 |
Convolution2d bakward: incorrect parameter kernelSize1
|
ErrorIncorrectKernelSise2 |
Convolution2d bakward: incorrect parameter kernelSize2
|
ErrorRidgeRegressionInternal |
Ridge Regression internal error
|
ErrorRidgeRegressionNormEqSystemSolutionFailed |
Failed to solve the system of normal equations
|
ErrorRidgeRegressionInvertFailed |
Failed to invert matrix
|
ErrorInconsistenceModelAndBatchSizeInParameter |
Inconsistence of model and batch size parameter in optimization solver
|
ErrorNeuralNetworkLayerCall |
Error in neural network layer call
|
ErrorSplitLayerBackward |
Error in split layer backward
|
ErrorPivotedQRInternal |
Pivoted QR internal error
|
ErrorDFBootstrapVarImportanceIncompatible |
Parameter 'bootstrap' is incompatible with requested variable importance type
|
ErrorDFBootstrapOOBIncompatible |
Parameter 'bootstrap' is incompatible with requested OOB result (no out-of-bag observations)
|
ErrorGbtIncorrectNumberOfTrees |
Number of trees in the model is not consistent with the number of classes
|
ErrorGbtPredictIncorrectNumberOfIterations |
Number of iterations value in GBT parameter is not consistent with the model
|
ErrorUserAllocatedMemory |
Couldn't free memory allocated by user
|
ErrorDataSourseNotAvailable |
ErrorDataSourseNotAvailable
|
ErrorHandlesSQL |
ErrorHandlesSQL
|
ErrorODBC |
ErrorODBC
|
ErrorSQLstmtHandle |
ErrorSQLstmtHandle
|
ErrorOnFileOpen |
Error on file open
|
ErrorOnFileRead |
Error on file read
|
ErrorNullByteInjection |
Error null byte injection
|
ErrorKDBNoConnection |
ErrorKDBNoConnection
|
ErrorKDBWrongCredentials |
ErrorKDBWrongCredentials
|
ErrorKDBNetworkError |
ErrorKDBNetworkError
|
ErrorKDBServerError |
ErrorKDBServerError
|
ErrorKDBTypeUnsupported |
ErrorKDBTypeUnsupported
|
ErrorKDBWrongTypeOfOutput |
ErrorKDBWrongTypeOfOutput
|
ErrorIncorrectEngineParameter |
Incorrect engine parameter in distribution
|
ErrorEmptyInputAlgorithmsCollection |
Input algorithms collection is empty
|
ErrorObjectDoesNotSupportSerialization |
SerializationIface is not implemented or implemented incorrectly
|
ErrorCouldntAttachCurrentThreadToJavaVM |
Couldn't attach current thread to Java VM
|
ErrorCouldntCreateGlobalReferenceToJavaObject |
Couldn't create global reference to Java object
|
ErrorCouldntFindJavaMethod |
Couldn't find Java method
|
ErrorCouldntFindClassForJavaObject |
Couldn't find class for Java object
|
ErrorCouldntDetachCurrentThreadFromJavaVM |
Couldn't detach current thread from Java VM
|
UnknownError |
Unknown error
|
NoErrorMessageFound |
No error message found
|
ErrorMethodNotImplemented |
Method is not implemented in the present library version
|
ErrorIncorrectOffset |
Incorrect offset
|
ErrorIterativeSolverIncorrectMaxNumberOfIterations |
Incorrect maximum number of iterations value in solver
|
ErrorIncorrectNumberOfTerms |
Incorrect number of summands (terms) in objective function
|
ErrorIncorrectNumberOfNodes |
Incorrect number of nodes
|