Skip to main content
Ctrl+K

anomalearn 0.0.2 documentation

Site Navigation

  • Getting started
  • User guide
  • API Reference
  • Developer guide
  • Release notes

Site Navigation

  • Getting started
  • User guide
  • API Reference
  • Developer guide
  • Release notes

Section Navigation

  • The importance of interfaces
  • Consistency in code
  • Discuss changes, take part
  • File naming
  • Code conventions
  • Tools for development
  • Documentation and documenting code
  • Testing functions and classes
  • UML diagrams for classes
  • anomalearn package
    • applications package
      • ExperimentLoader module
        • ExperimentLoader
      • IExperimentLoader module
        • IExperimentLoader
    • input_validation package
      • array_checks module
        • check_array_1d
        • check_array_general
        • check_x_y_smaller_1d
      • colors module
        • is_matplotlib_color
      • attribute_checks module
        • check_argument_types
        • check_attributes_exist
        • check_not_default_attributes
        • is_var_of_type
    • analysis package
      • stationarity module
        • analyse_stationarity
      • decomposition module
        • decompose_time_series
      • dataset_simplicity module
        • __module_logger
        • _analyse_constant_simplicity
        • _check_analysis_inputs
        • _diff_numpy
        • _execute_movement_simplicity
        • _fast_execute_mixed_score_simplicity
        • _fast_execute_movement_simplicity
        • _find_best_constants
        • _find_constant_score
        • _fix_numba_upper_lower
        • _get_windows_to_try
        • _transpose_numpy
        • analyse_constant_simplicity
        • analyse_mixed_simplicity
        • analyse_mov_avg_simplicity
        • analyse_mov_std_simplicity
    • visualizer package
      • time_series package
        • decomposition module
          • plot_time_series_decomposition
        • correlation module
          • plot_correlation_functions
      • scatter_plots module
        • scatter_plot
      • line_plots module
        • __check_common_line_params
        • __line_plot
        • __set_lim
        • confidence_line_plot
        • line_plot
      • bar_plots module
        • bar_class_distribution
        • bar_plot
      • box_plots module
        • box_plot
      • pie_plots module
        • pie_class_distribution
        • pie_plot
    • reader package
      • time_series package
        • NASAReader module
          • NASAReader
        • SMDReader module
          • SMDReader
        • NABReader module
          • NABReader
        • KitsuneReader module
          • KitsuneReader
        • config module
          • rts_config
        • ODINTSReader module
          • ODINTSReader
        • YahooS5Reader module
          • YahooS5Reader
        • TSBenchmarkReader module
          • TSBenchmarkReader
        • GHLReader module
          • GHLReader
        • ExathlonReader module
          • ExathlonReader
        • UCRReader module
          • UCRReader
        • MGABReader module
          • MGABReader
        • TSReader module
          • TSReader
        • TSMultipleReader module
          • TSMultipleReader
      • IDataReader module
        • IDataReader
      • IDatasetReader module
        • IDatasetReader
      • IDataMultipleReader module
        • IDataMultipleReader
    • exceptions package
      • OpenClosedRangeError module
        • OpenClosedRangeError
      • RangeError module
        • RangeError
      • NotTrainedError module
        • NotTrainedError
      • ClosedOpenRangeError module
        • ClosedOpenRangeError
      • SelectionError module
        • SelectionError
      • InvalidInputShape module
        • InvalidInputShape
      • OpenRangeError module
        • OpenRangeError
      • ClosedRangeError module
        • ClosedRangeError
    • utils package
      • estimation module
        • __module_logger
        • estimate_mean_covariance
      • json module
        • load_py_json
        • save_py_json
      • numpy module
        • are_random_state_equal
      • scikit module
        • __module_logger
        • _get_property
        • are_list_attr_equal
        • are_normal_attr_equal
        • are_numpy_attr_equal
        • are_random_state_attr_equal
        • are_tree_attr_equal
      • moving_functions module
        • _mov_avg
        • _mov_std
        • mov_avg
        • mov_std
      • filesystem module
        • __module_logger
        • find_or_create_dir
      • arrays module
        • get_rows_without_nan
      • lists module
        • __module_logger
        • all_indices
        • concat_list_array
      • metrics module
        • __module_logger
        • _binary_confusion_matrix
        • _check_binary_input
        • _true_negative_rate
        • _true_positive_rate
        • binary_confusion_matrix
        • true_negative_rate
        • true_positive_rate
    • algorithms package
      • models package
        • neural package
        • statistical package
        • machine_learning package
          • IsolationForest module
            • IsolationForest
        • IAnomalyScorer module
          • IAnomalyScorer
      • preprocessing package
        • SlidingWindowReconstruct module
          • SlidingWindowReconstruct
        • SlidingWindowForecast module
          • SlidingWindowForecast
      • tuning package
        • hyperparameter package
          • GaussianProcessesSearch module
            • GaussianProcessesSearch
          • IHyperparameterSearch module
            • IHyperparameterSearch
          • IHyperparameterSearchResults module
            • IHyperparameterSearchResults
          • HyperparameterSearchResults module
            • HyperparameterSearchResults
          • TimeSeriesGridSearch module
            • TimeSeriesGridSearch
          • GBRTSearch module
            • GBRTSearch
          • HyperparameterSearch module
            • HyperparameterSearch
          • SkoptSearchABC module
            • SkoptSearchABC
          • ForestSearch module
            • ForestSearch
        • ICrossValidation module
          • ICrossValidation
      • transformers package
        • StandardScaler module
          • StandardScaler
        • MinMaxScaler module
          • MinMaxScaler
      • pipelines package
        • AbstractPipelineSavableLayer module
          • AbstractPipelineSavableLayer
        • IPipeline module
          • IPipeline
        • IPipelineLayer module
          • IPipelineLayer
        • AbstractPipelineBaseLayer module
          • AbstractPipelineBaseLayer
        • Pipeline module
          • Pipeline
      • postprocessing package
        • ThresholdMaxOnNormal module
          • ThresholdMaxOnNormal
        • BuilderVectorsSlidingWindow module
          • BuilderVectorsSlidingWindow
        • BuilderErrorVectorsDifference module
          • BuilderErrorVectorsDifference
        • ScorerGaussian module
          • ScorerGaussian
        • ScorerMahalanobis module
          • ScorerMahalanobis
        • BuilderErrorVectorsAbsDifference module
          • BuilderErrorVectorsAbsDifference
        • BuilderErrorVectorsNorm module
          • BuilderErrorVectorsNorm
      • IParametric module
        • IParametric
      • ISavable module
        • ISavable
      • algo_functions module
        • __module_logger
        • _find_class_in_lib
        • instantiate_estimator
        • load_estimator
      • IRegressor module
        • IRegressor
      • BaseModel module
        • BaseModel
      • ICopyable module
        • ICopyable
      • IShapeChanger module
        • IShapeChanger
      • IProbabilisticClassifier module
        • IProbabilisticClassifier
      • ICluster module
        • ICluster
      • ITransformer module
        • ITransformer
      • IMultipleParametric module
        • IMultipleParametric
      • IPredictor module
        • IPredictor
      • SavableModel module
        • SavableModel
      • IClassifier module
        • IClassifier
      • IBoundaryClassifier module
        • IBoundaryClassifier
    • abc module
      • __module_logger
      • _check_methods
      • EqualityABC
      • FullyRepresentableABC
      • ObtainableABC
      • RepresentableABC
      • StringableABC
  • Poetry
  • Formatters
  • Linters
  • Create the documentation
  • Pull requests: how to manage them
  • Developer guide
  • utils package
  • estimation module

estimation module#

Attributes

__module_logger

Instances of the Logger class represent a single logging channel.

Functions

estimate_mean_covariance(x)

Estimates mean and covariance matrix.

previous

utils package

next

__module_logger
Show Source

© Copyright 2023, Marco Petri.

Created using Sphinx 6.1.3.

Built with the PyData Sphinx Theme 0.13.3.