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External module "src/model"

Index

Enumerations

Classes

Interfaces

Type aliases

Functions

Object literals

Type aliases

ClassificationEvaluation

ClassificationEvaluation: { accuracy: number; actuals: ModelXDataTypes.Vector; estimates: ModelXDataTypes.Vector; labels: string[]; matrix: ModelXDataTypes.Matrix }

Type declaration

  • accuracy: number
  • actuals: ModelXDataTypes.Vector
  • estimates: ModelXDataTypes.Vector
  • labels: string[]
  • matrix: ModelXDataTypes.Matrix

CrossValidationOptions

CrossValidationOptions: { folds?: number; parse_int_train_size?: boolean; random_state?: number; return_array?: boolean; test_size?: number; train_size?: number }

Type declaration

  • Optional folds?: number
  • Optional parse_int_train_size?: boolean
  • Optional random_state?: number
  • Optional return_array?: boolean
  • Optional test_size?: number
  • Optional train_size?: number

DataFilterFunction

DataFilterFunction: (datum: ModelXDataTypes.Datum, datumIndex: number) => boolean

Type declaration

    • (datum: ModelXDataTypes.Datum, datumIndex: number): boolean

    • Parameters

      • datum: ModelXDataTypes.Datum
      • datumIndex: number

      Returns boolean

EvaluateClassificationModel

EvaluateClassificationModel: {}

Type declaration

EvaluateModelOptions

EvaluateModelOptions: { predictionOptions?: PredictionOptions; retrain?: boolean; x_indep_matrix_test?: ModelXDataTypes.Matrix; y_dep_matrix_test?: ModelXDataTypes.Matrix }

Type declaration

  • Optional predictionOptions?: PredictionOptions
  • Optional retrain?: boolean
  • Optional x_indep_matrix_test?: ModelXDataTypes.Matrix
  • Optional y_dep_matrix_test?: ModelXDataTypes.Matrix

EvaluateRegressionModel

EvaluateRegressionModel: {}

Type declaration

EvaluationAccuracyOptions

EvaluationAccuracyOptions: { actualsDescaled?: ModelXDataTypes.Data; dependent_feature_label?: string; estimatesDescaled?: ModelXDataTypes.Data }

Type declaration

  • Optional actualsDescaled?: ModelXDataTypes.Data
  • Optional dependent_feature_label?: string
  • Optional estimatesDescaled?: ModelXDataTypes.Data

ForecastHelperNextValueData

ForecastHelperNextValueData: { associated_data_entity?: string; associated_data_location?: string; associated_data_product?: string; date?: Date; forecast_entity_id?: string; forecast_entity_name?: string; forecast_entity_title?: string; forecast_entity_type?: string; origin_time_zone?: string } & ModelXDataTypes.Datum

ForecastPredictionInputNextValueFunction

ForecastPredictionInputNextValueFunction: (state: ForecastPredictionNextValueState) => ModelXDataTypes.Datum

returns a Datum used in next forecast prediction input

Type declaration

ForecastPredictionNextValueState

ForecastPredictionNextValueState: { DataSet: DataSet; data: ModelXDataTypes.Data; existingDatasetObjectIndex: number; forecastDate?: Date; forecastDates?: Date[]; forecastPredictionIndex?: number; isOpen?: (...args: any[]) => BooleanAnswer; isOutlier?: (...args: any[]) => BooleanAnswer; lastDataRow?: ModelXDataTypes.Datum; parsedDate?: ParsedDate; rawInputPredictionObject?: ModelXDataTypes.Datum; reverseTransform?: boolean; sumPreviousRows?: sumPreviousRows; unscaledLastForecastedValue?: ModelXDataTypes.Datum }

Type declaration

  • DataSet: DataSet
  • data: ModelXDataTypes.Data
  • existingDatasetObjectIndex: number
  • Optional forecastDate?: Date
  • Optional forecastDates?: Date[]
  • Optional forecastPredictionIndex?: number
  • Optional isOpen?: (...args: any[]) => BooleanAnswer
  • Optional isOutlier?: (...args: any[]) => BooleanAnswer
  • Optional lastDataRow?: ModelXDataTypes.Datum
  • Optional parsedDate?: ParsedDate
  • Optional rawInputPredictionObject?: ModelXDataTypes.Datum
  • Optional reverseTransform?: boolean
  • Optional sumPreviousRows?: sumPreviousRows
  • Optional unscaledLastForecastedValue?: ModelXDataTypes.Datum

GeneratedFunctionDefinitionsList

GeneratedFunctionDefinitionsList: GeneratedStatefulFunctionObject[]

GeneratedFunctionDefinitionsObject

GeneratedFunctionDefinitionsObject: {}

Type declaration

GeneratedStatefulFunction

GeneratedStatefulFunction: (state: GeneratedStatefulFunctionState) => number

Type declaration

GeneratedStatefulFunctionObject

GeneratedStatefulFunctionObject: { function_body: string; variable_name: string }

Type declaration

  • function_body: string
  • variable_name: string

GeneratedStatefulFunctionParams

GeneratedStatefulFunctionParams: { function_name_prefix?: string; props?: GeneratedStatefulFunctionProps } & GeneratedStatefulFunctionObject

GeneratedStatefulFunctionProps

GeneratedStatefulFunctionProps: { Luxon: any; ModelXData: any }

Type declaration

  • Luxon: any
  • ModelXData: any

GeneratedStatefulFunctionState

GeneratedStatefulFunctionState: any

GeneratedStatefulFunctions

GeneratedStatefulFunctions: {}

Type declaration

GetDataSetProperties

GetDataSetProperties: { DataSetData?: ModelXDataTypes.Data; dimension?: Dimensions; nextValueIncludeDateProperty?: boolean; nextValueIncludeForecastAssociations?: boolean; nextValueIncludeForecastDate?: boolean; nextValueIncludeForecastInputs?: boolean; nextValueIncludeForecastTimezone?: boolean; nextValueIncludeLocalParsedDate?: boolean; nextValueIncludeParsedDate?: boolean }

Type declaration

  • Optional DataSetData?: ModelXDataTypes.Data
  • Optional dimension?: Dimensions
  • Optional nextValueIncludeDateProperty?: boolean
  • Optional nextValueIncludeForecastAssociations?: boolean
  • Optional nextValueIncludeForecastDate?: boolean
  • Optional nextValueIncludeForecastInputs?: boolean
  • Optional nextValueIncludeForecastTimezone?: boolean
  • Optional nextValueIncludeLocalParsedDate?: boolean
  • Optional nextValueIncludeParsedDate?: boolean

ModelConfiguration

ModelConfiguration: { DataSet?: DataSet; Model?: TensorScriptModelInterface; auto_assign_features?: boolean; cross_validation_options?: CrossValidationOptions; debug?: boolean; dependent_variables?: string[]; dimension?: Dimensions; emptyObject?: ModelXDataTypes.Datum; entity?: Entity; independent_variables?: string[]; input_independent_features?: AutoFeature[]; max_evaluation_outputs?: number; mockEncodedData?: ModelXDataTypes.Data; model_category?: ModelCategories; model_type: ModelTypes; next_value_functions?: GeneratedFunctionDefinitionsList; output_dependent_features?: AutoFeature[]; prediction_inputs?: ModelXDataTypes.Data; prediction_inputs_next_value_functions?: GeneratedFunctionDefinitionsList; prediction_options?: PredictModelConfig; prediction_timeseries_date_feature?: string; prediction_timeseries_date_format?: string; prediction_timeseries_dimension_feature?: string; prediction_timeseries_end_date?: Date | string; prediction_timeseries_start_date?: Date | string; prediction_timeseries_time_zone?: string; preprocessing_feature_column_options?: ModelXDataTypes.DataSetTransform; retrain_forecast_model_with_predictions?: boolean; testDataSet?: DataSet; trainDataSet?: DataSet; trainingData?: ModelXDataTypes.Data; training_data_filter_function?: DataFilterFunction; training_data_filter_function_body?: string; training_feature_column_options?: ModelXDataTypes.DataSetTransform; training_options?: ModelXModelTypes.TensorScriptOptions; training_progress_callback?: TrainingProgressCallback; training_size_values?: number; use_cache?: boolean; use_mock_dates_to_fit_trainning_data?: boolean; use_preprocessing_on_trainning_data?: boolean; validate_training_data?: boolean; x_indep_matrix_test?: ModelXDataTypes.Matrix; x_indep_matrix_train?: ModelXDataTypes.Matrix; x_independent_features?: string[]; x_raw_independent_features?: string[]; y_dep_matrix_test?: ModelXDataTypes.Matrix; y_dep_matrix_train?: ModelXDataTypes.Matrix; y_dependent_labels?: string[]; y_raw_dependent_labels?: string[] }

Type declaration

  • Optional DataSet?: DataSet
  • Optional Model?: TensorScriptModelInterface
  • Optional auto_assign_features?: boolean
  • Optional cross_validation_options?: CrossValidationOptions
  • Optional debug?: boolean
  • Optional dependent_variables?: string[]
  • Optional dimension?: Dimensions
  • Optional emptyObject?: ModelXDataTypes.Datum
  • Optional entity?: Entity
  • Optional independent_variables?: string[]
  • Optional input_independent_features?: AutoFeature[]
  • Optional max_evaluation_outputs?: number
  • Optional mockEncodedData?: ModelXDataTypes.Data
  • Optional model_category?: ModelCategories
  • model_type: ModelTypes
  • Optional next_value_functions?: GeneratedFunctionDefinitionsList
  • Optional output_dependent_features?: AutoFeature[]
  • Optional prediction_inputs?: ModelXDataTypes.Data
  • Optional prediction_inputs_next_value_functions?: GeneratedFunctionDefinitionsList
  • Optional prediction_options?: PredictModelConfig
  • Optional prediction_timeseries_date_feature?: string
  • Optional prediction_timeseries_date_format?: string
  • Optional prediction_timeseries_dimension_feature?: string
  • Optional prediction_timeseries_end_date?: Date | string
  • Optional prediction_timeseries_start_date?: Date | string
  • Optional prediction_timeseries_time_zone?: string
  • Optional preprocessing_feature_column_options?: ModelXDataTypes.DataSetTransform
  • Optional retrain_forecast_model_with_predictions?: boolean
  • Optional testDataSet?: DataSet
  • Optional trainDataSet?: DataSet
  • Optional trainingData?: ModelXDataTypes.Data
  • Optional training_data_filter_function?: DataFilterFunction
  • Optional training_data_filter_function_body?: string
  • Optional training_feature_column_options?: ModelXDataTypes.DataSetTransform
  • Optional training_options?: ModelXModelTypes.TensorScriptOptions
  • Optional training_progress_callback?: TrainingProgressCallback
  • Optional training_size_values?: number
  • Optional use_cache?: boolean
  • Optional use_mock_dates_to_fit_trainning_data?: boolean
  • Optional use_preprocessing_on_trainning_data?: boolean
  • Optional validate_training_data?: boolean
  • Optional x_indep_matrix_test?: ModelXDataTypes.Matrix
  • Optional x_indep_matrix_train?: ModelXDataTypes.Matrix
  • Optional x_independent_features?: string[]
  • Optional x_raw_independent_features?: string[]
  • Optional y_dep_matrix_test?: ModelXDataTypes.Matrix
  • Optional y_dep_matrix_train?: ModelXDataTypes.Matrix
  • Optional y_dependent_labels?: string[]
  • Optional y_raw_dependent_labels?: string[]

ModelOptions

ModelOptions: { trainingData?: ModelXDataTypes.Data }

Type declaration

  • Optional trainingData?: ModelXDataTypes.Data

ModelStatus

ModelStatus: { lastTrained?: Date; trained: boolean }

Type declaration

  • Optional lastTrained?: Date
  • trained: boolean

ModelTrainningOptions

ModelTrainningOptions: { cross_validate_training_data?: boolean; fixPredictionDates?: boolean; getPredictionInputPromise?: GetPredicitonData; prediction_inputs?: ModelXDataTypes.Data; retrain?: boolean; trainingData?: ModelXDataTypes.Data; use_mock_dates_to_fit_trainning_data?: boolean; use_next_value_functions_for_training_data?: boolean }

Type declaration

  • Optional cross_validate_training_data?: boolean
  • Optional fixPredictionDates?: boolean
  • Optional getPredictionInputPromise?: GetPredicitonData
  • Optional prediction_inputs?: ModelXDataTypes.Data
  • Optional retrain?: boolean
  • Optional trainingData?: ModelXDataTypes.Data
  • Optional use_mock_dates_to_fit_trainning_data?: boolean
  • Optional use_next_value_functions_for_training_data?: boolean

PredictModelConfig

PredictModelConfig: { probability?: boolean }

Type declaration

  • Optional probability?: boolean

PredictModelOptions

PredictModelOptions: { descalePredictions?: boolean; getPredictionInputPromise?: GetPredicitonData; includeEvaluation?: boolean; includeInputs?: boolean; predictionOptions?: PredictionOptions; prediction_inputs?: ModelXDataTypes.Data; retrain?: boolean }

Type declaration

  • Optional descalePredictions?: boolean
  • Optional getPredictionInputPromise?: GetPredicitonData
  • Optional includeEvaluation?: boolean
  • Optional includeInputs?: boolean
  • Optional predictionOptions?: PredictionOptions
  • Optional prediction_inputs?: ModelXDataTypes.Data
  • Optional retrain?: boolean

PredictionOptions

PredictionOptions: {}

Type declaration

  • [index: string]: any

RegressionEvaluation

RegressionEvaluation: { accuracyPercentage: number; actuals: ModelXDataTypes.Vector; adjustedRSquared: number; estimates: ModelXDataTypes.Vector; meanAbsoluteDeviation: number; meanAbsolutePercentageError: number; meanForecastError: number; meanSquaredError: number; metric: string; originalMeanAbsolutePercentageError: number; rSquared: number; reason: string; standardError: number; trackingSignal: number }

Type declaration

  • accuracyPercentage: number
  • actuals: ModelXDataTypes.Vector
  • adjustedRSquared: number
  • estimates: ModelXDataTypes.Vector
  • meanAbsoluteDeviation: number
  • meanAbsolutePercentageError: number
  • meanForecastError: number
  • meanSquaredError: number
  • metric: string
  • originalMeanAbsolutePercentageError: number
  • rSquared: number
  • reason: string
  • standardError: number
  • trackingSignal: number

SumPreviousRowContext

SumPreviousRowContext: { DataSet: DataSet; data: ModelXDataTypes.Data; debug?: boolean; offset: number; reverseTransform?: boolean }

Type declaration

  • DataSet: DataSet
  • data: ModelXDataTypes.Data
  • Optional debug?: boolean
  • offset: number
  • Optional reverseTransform?: boolean

SumPreviousRowsOptions

SumPreviousRowsOptions: { offset: number; property: string; rows: number }

Type declaration

  • offset: number
  • property: string
  • rows: number

TimeseriesDimension

TimeseriesDimension: { dateFormat?: string; dimension: Dimensions }

Type declaration

  • Optional dateFormat?: string
  • dimension: Dimensions

ValidateTimeseriesDataOptions

ValidateTimeseriesDataOptions: { fixPredictionDates?: boolean; getPredictionInputPromise?: GetPredicitonData; predictionOptions?: PredictionOptions; prediction_inputs?: ModelXDataTypes.Data }

Type declaration

  • Optional fixPredictionDates?: boolean
  • Optional getPredictionInputPromise?: GetPredicitonData
  • Optional predictionOptions?: PredictionOptions
  • Optional prediction_inputs?: ModelXDataTypes.Data

retrainTimeseriesModel

retrainTimeseriesModel: { fitOptions?: {}; inputMatrix?: ModelXModelTypes.Matrix; predictionMatrix?: ModelXModelTypes.Matrix }

Type declaration

  • Optional fitOptions?: {}
    • [index: string]: any
  • Optional inputMatrix?: ModelXModelTypes.Matrix
  • Optional predictionMatrix?: ModelXModelTypes.Matrix

Functions

getGeneratedStatefulFunction

  • getGeneratedStatefulFunction(__namedParameters: { function_body: string; function_name_prefix: string; props: { Luxon: any; ModelXData: any }; variable_name: string }): GeneratedStatefulFunction

  • Takes an object that describes a function to be created from a function body string

    example

    getGeneratedStatefulFunction({ variable_name='myFunctionName', function_body='return 3', function_name_prefix='customFunction_', }) => function customFunction_myFunctionName(state){ 'use strict'; return 3; }

    Parameters

    • __namedParameters: { function_body: string; function_name_prefix: string; props: { Luxon: any; ModelXData: any }; variable_name: string }
      • function_body: string
      • function_name_prefix: string
      • props: { Luxon: any; ModelXData: any }
        • Luxon: any
        • ModelXData: any
      • variable_name: string

    Returns GeneratedStatefulFunction

sumPreviousRows

Object literals

Const modelCategoryMap

modelCategoryMap: object

__computed

__computed: ModelCategories = ModelCategories.DECISION

Const modelMap

modelMap: object

ai-classification

ai-classification: DeepLearningClassification = ModelXModel.DeepLearningClassification

ai-fast-forecast

ai-fast-forecast: LSTMTimeSeries = ModelXModel.LSTMTimeSeries

ai-forecast

ai-forecast: LSTMMultivariateTimeSeries = ModelXModel.LSTMMultivariateTimeSeries

ai-linear-regression

ai-linear-regression: MultipleLinearRegression = ModelXModel.MultipleLinearRegression

ai-logistic-classification

ai-logistic-classification: LogisticRegression = ModelXModel.LogisticRegression

ai-regression

ai-regression: DeepLearningRegression = ModelXModel.DeepLearningRegression

ai-timeseries-regression-forecast

ai-timeseries-regression-forecast: MultipleLinearRegression = ModelXModel.MultipleLinearRegression