| 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
|
| ErrorCpuIsInvalid |
Invalid CPU value used
|
| ErrorCpuNotSupported |
CPU not supported
|
| ErrorMemoryAllocationFailed |
Memory allocation failed
|
| ErrorEmptyDataBlock |
Empty data block
|
| 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
|
| 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
|
| 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.
|
| 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
|
| 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
|