TimeSmith

Contents:

  • Installation
    • Optional Dependencies
    • Development Installation
  • Getting Started
    • Creating Data
    • Defining a Task
    • Choosing a Forecaster
    • Running a Backtest
    • Using Pipelines
    • Summary
  • Architecture
  • Design Decisions
  • API Reference
    • Core Modules
      • BaseDetector
        • BaseDetector.predict()
        • BaseDetector.score()
      • BaseEstimator
        • BaseEstimator.__init__()
        • BaseEstimator.fit()
        • BaseEstimator.is_fitted
      • BaseFeaturizer
        • BaseFeaturizer.transform()
      • BaseForecaster
        • BaseForecaster.predict()
        • BaseForecaster.predict_interval()
      • BaseObject
        • BaseObject.clone()
        • BaseObject.get_params()
        • BaseObject.set_params()
      • BaseTransformer
        • BaseTransformer.fit_transform()
        • BaseTransformer.inverse_transform()
        • BaseTransformer.transform()
      • BayesianChangePointDetector
        • BayesianChangePointDetector.__init__()
        • BayesianChangePointDetector.fit()
        • BayesianChangePointDetector.predict()
        • BayesianChangePointDetector.score()
      • ButterworthFilter
        • ButterworthFilter.__init__()
        • ButterworthFilter.fit()
        • ButterworthFilter.transform()
      • CUSUMDetector
        • CUSUMDetector.__init__()
        • CUSUMDetector.fit()
        • CUSUMDetector.predict()
        • CUSUMDetector.score()
      • DecomposeTransformer
        • DecomposeTransformer.__init__()
        • DecomposeTransformer.fit()
        • DecomposeTransformer.get_components()
        • DecomposeTransformer.inverse_transform()
        • DecomposeTransformer.transform()
      • DegradationRateFeaturizer
        • DegradationRateFeaturizer.__init__()
        • DegradationRateFeaturizer.fit()
        • DegradationRateFeaturizer.transform()
      • DeseasonalizeTransformer
        • DeseasonalizeTransformer.__init__()
        • DeseasonalizeTransformer.fit()
        • DeseasonalizeTransformer.inverse_transform()
        • DeseasonalizeTransformer.transform()
      • DetrendTransformer
        • DetrendTransformer.__init__()
        • DetrendTransformer.fit()
        • DetrendTransformer.inverse_transform()
        • DetrendTransformer.transform()
      • DifferencingFeaturizer
        • DifferencingFeaturizer.__init__()
        • DifferencingFeaturizer.fit()
        • DifferencingFeaturizer.transform()
      • HampelOutlierRemover
        • HampelOutlierRemover.__init__()
        • HampelOutlierRemover.fit()
        • HampelOutlierRemover.transform()
      • IsolationForestOutlierRemover
        • IsolationForestOutlierRemover.__init__()
        • IsolationForestOutlierRemover.fit()
        • IsolationForestOutlierRemover.transform()
      • LagFeaturizer
        • LagFeaturizer.__init__()
        • LagFeaturizer.fit()
        • LagFeaturizer.transform()
      • MissingDateFiller
        • MissingDateFiller.__init__()
        • MissingDateFiller.fit()
        • MissingDateFiller.transform()
      • MissingValueFiller
        • MissingValueFiller.__init__()
        • MissingValueFiller.fit()
        • MissingValueFiller.transform()
      • OutlierRemover
        • OutlierRemover.__init__()
        • OutlierRemover.fit()
        • OutlierRemover.transform()
      • PELTDetector
        • PELTDetector.__init__()
        • PELTDetector.fit()
        • PELTDetector.predict()
        • PELTDetector.score()
      • Resampler
        • Resampler.__init__()
        • Resampler.fit()
        • Resampler.transform()
      • RollingFeaturizer
        • RollingFeaturizer.__init__()
        • RollingFeaturizer.fit()
        • RollingFeaturizer.transform()
      • SavitzkyGolayFilter
        • SavitzkyGolayFilter.__init__()
        • SavitzkyGolayFilter.fit()
        • SavitzkyGolayFilter.transform()
      • SeasonalBaselineDetector
        • SeasonalBaselineDetector.__init__()
        • SeasonalBaselineDetector.fit()
        • SeasonalBaselineDetector.predict()
        • SeasonalBaselineDetector.score()
      • SeasonalFeaturizer
        • SeasonalFeaturizer.__init__()
        • SeasonalFeaturizer.fit()
        • SeasonalFeaturizer.transform()
      • TimeFeaturizer
        • TimeFeaturizer.__init__()
        • TimeFeaturizer.fit()
        • TimeFeaturizer.transform()
      • VotingEnsembleDetector
        • VotingEnsembleDetector.__init__()
        • VotingEnsembleDetector.fit()
        • VotingEnsembleDetector.predict()
        • VotingEnsembleDetector.score()
      • WaveletDenoiser
        • WaveletDenoiser.__init__()
        • WaveletDenoiser.fit()
        • WaveletDenoiser.transform()
      • WaveletDetector
        • WaveletDetector.__init__()
        • WaveletDetector.fit()
        • WaveletDetector.get_wavelet_coefficients()
        • WaveletDetector.predict()
        • WaveletDetector.score()
      • ZScoreOutlierRemover
        • ZScoreOutlierRemover.__init__()
        • ZScoreOutlierRemover.fit()
        • ZScoreOutlierRemover.transform()
      • detect_seasonality()
      • detect_trend()
      • get_tags()
      • preprocess_for_changepoint()
      • set_tags()
      • validate_input()
    • Forecasters
      • ARIMAForecaster
        • ARIMAForecaster.__init__()
        • ARIMAForecaster.fit()
        • ARIMAForecaster.get_order()
        • ARIMAForecaster.predict()
        • ARIMAForecaster.predict_interval()
      • BayesianForecaster
        • BayesianForecaster.__init__()
        • BayesianForecaster.fit()
        • BayesianForecaster.get_posterior_summary()
        • BayesianForecaster.predict()
        • BayesianForecaster.predict_interval()
      • BlackScholesMonteCarloForecaster
        • BlackScholesMonteCarloForecaster.__init__()
        • BlackScholesMonteCarloForecaster.fit()
        • BlackScholesMonteCarloForecaster.predict()
        • BlackScholesMonteCarloForecaster.predict_interval()
      • EnsembleForecaster
        • EnsembleForecaster.__init__()
        • EnsembleForecaster.fit()
        • EnsembleForecaster.predict()
      • ExponentialMovingAverageForecaster
        • ExponentialMovingAverageForecaster.__init__()
        • ExponentialMovingAverageForecaster.fit()
        • ExponentialMovingAverageForecaster.predict()
      • ExponentialSmoothingForecaster
        • ExponentialSmoothingForecaster.__init__()
        • ExponentialSmoothingForecaster.fit()
        • ExponentialSmoothingForecaster.predict()
        • ExponentialSmoothingForecaster.predict_interval()
      • KalmanFilterForecaster
        • KalmanFilterForecaster.__init__()
        • KalmanFilterForecaster.fit()
        • KalmanFilterForecaster.predict()
        • KalmanFilterForecaster.predict_interval()
      • LSTMForecaster
        • LSTMForecaster.__init__()
        • LSTMForecaster.fit()
        • LSTMForecaster.predict()
        • LSTMForecaster.predict_interval()
      • LinearTrendForecaster
        • LinearTrendForecaster.__init__()
        • LinearTrendForecaster.fit()
        • LinearTrendForecaster.predict()
      • MonteCarloForecaster
        • MonteCarloForecaster.__init__()
        • MonteCarloForecaster.fit()
        • MonteCarloForecaster.predict()
        • MonteCarloForecaster.predict_interval()
      • SimpleMovingAverageForecaster
        • SimpleMovingAverageForecaster.__init__()
        • SimpleMovingAverageForecaster.fit()
        • SimpleMovingAverageForecaster.predict()
      • SyntheticControlForecaster
        • SyntheticControlForecaster.__init__()
        • SyntheticControlForecaster.fit()
        • SyntheticControlForecaster.get_weights()
        • SyntheticControlForecaster.predict()
      • VARForecaster
        • VARForecaster.__init__()
        • VARForecaster.fit()
        • VARForecaster.predict()
        • VARForecaster.predict_interval()
      • WeightedMovingAverageForecaster
        • WeightedMovingAverageForecaster.__init__()
        • WeightedMovingAverageForecaster.fit()
        • WeightedMovingAverageForecaster.predict()
    • Network Analysis
      • Graph
        • Graph.edges
        • Graph.n_nodes
        • Graph.directed
        • Graph.weighted
        • Graph.__init__()
        • Graph.adjacency_matrix()
        • Graph.as_networkx()
        • Graph.degree_sequence()
        • Graph.in_degree_sequence()
        • Graph.n_edges
        • Graph.out_degree_sequence()
        • Graph.summary()
      • HVGFeaturizer
        • HVGFeaturizer.__init__()
        • HVGFeaturizer.fit()
        • HVGFeaturizer.transform()
      • MultiscaleGraphs
        • MultiscaleGraphs.__init__()
        • MultiscaleGraphs.fit()
        • MultiscaleGraphs.fit_transform()
        • MultiscaleGraphs.scale_signature()
        • MultiscaleGraphs.stats()
      • NVGFeaturizer
        • NVGFeaturizer.__init__()
        • NVGFeaturizer.fit()
        • NVGFeaturizer.transform()
      • NetworkSignificanceResult
        • NetworkSignificanceResult.metric_name
        • NetworkSignificanceResult.observed_value
        • NetworkSignificanceResult.null_mean
        • NetworkSignificanceResult.null_std
        • NetworkSignificanceResult.z_score
        • NetworkSignificanceResult.p_value
        • NetworkSignificanceResult.n_surrogates
        • NetworkSignificanceResult.surrogate_method
        • NetworkSignificanceResult.significant
        • NetworkSignificanceResult.confidence_interval
        • NetworkSignificanceResult.__init__()
        • NetworkSignificanceResult.alpha
        • NetworkSignificanceResult.confidence_interval
        • NetworkSignificanceResult.metric_name
        • NetworkSignificanceResult.n_surrogates
        • NetworkSignificanceResult.null_mean
        • NetworkSignificanceResult.null_std
        • NetworkSignificanceResult.observed_value
        • NetworkSignificanceResult.p_value
        • NetworkSignificanceResult.significant
        • NetworkSignificanceResult.surrogate_method
        • NetworkSignificanceResult.z_score
      • RecurrenceNetworkFeaturizer
        • RecurrenceNetworkFeaturizer.__init__()
        • RecurrenceNetworkFeaturizer.fit()
        • RecurrenceNetworkFeaturizer.transform()
      • TransferEntropyDetector
        • TransferEntropyDetector.__init__()
        • TransferEntropyDetector.fit()
        • TransferEntropyDetector.predict()
        • TransferEntropyDetector.score()
      • TransitionNetworkFeaturizer
        • TransitionNetworkFeaturizer.__init__()
        • TransitionNetworkFeaturizer.fit()
        • TransitionNetworkFeaturizer.transform()
      • build_windows()
      • coarse_grain()
      • compute_clustering()
      • compute_modularity()
      • compute_network_metric_significance()
      • compute_path_lengths()
      • conditional_transfer_entropy()
      • directed_3node_motifs()
      • generate_surrogate()
      • graph_summary()
      • net_enn()
      • net_knn()
      • network_metrics()
      • node_roles()
      • transfer_entropy()
      • transfer_entropy_network()
      • ts_to_windows()
      • undirected_4node_motifs()
    • Utilities
      • autocorrelation()
      • autocorrelation_plot_data()
      • black_scholes_monte_carlo()
      • bootstrap_confidence_intervals()
      • compute_anomalies()
      • compute_climatology()
      • correlation_distance()
      • create_sequences()
      • create_sequences_with_exog()
      • cross_correlation_distance()
      • detect_anomalies_mad()
      • detect_extreme_events()
      • detect_frequency()
      • dtw_distance()
      • ensure_datetime_index()
      • euclidean_distance()
      • fill_missing_dates()
      • is_stationary()
      • load_ts_data()
      • manhattan_distance()
      • monte_carlo_simulation()
      • parametric_confidence_intervals()
      • partial_autocorrelation()
      • plot_autocorrelation()
      • plot_forecast()
      • plot_monte_carlo()
      • plot_monte_carlo_paths()
      • plot_multiple_series()
      • plot_residuals()
      • plot_timeseries()
      • remove_outliers_iqr()
      • resample_ts()
      • split_ts()
      • test_stationarity()
      • train_test_split()
    • Composition
      • Adapter
        • Adapter.transform()
      • FeatureUnion
        • FeatureUnion.featurizers
        • FeatureUnion.__init__()
        • FeatureUnion.fit()
        • FeatureUnion.get_params()
        • FeatureUnion.set_params()
        • FeatureUnion.transform()
      • ForecasterPipeline
        • ForecasterPipeline.steps
        • ForecasterPipeline.forecaster
        • ForecasterPipeline.__init__()
        • ForecasterPipeline.fit()
        • ForecasterPipeline.get_params()
        • ForecasterPipeline.predict()
        • ForecasterPipeline.predict_interval()
        • ForecasterPipeline.set_params()
      • Pipeline
        • Pipeline.steps
        • Pipeline.__init__()
        • Pipeline.fit()
        • Pipeline.get_params()
        • Pipeline.inverse_transform()
        • Pipeline.set_params()
        • Pipeline.transform()
      • make_forecaster_pipeline()
      • make_pipeline()
    • Evaluation
      • ExpandingWindowSplit
        • ExpandingWindowSplit.initial_window
        • ExpandingWindowSplit.step_size
        • ExpandingWindowSplit.fh
        • ExpandingWindowSplit.__init__()
        • ExpandingWindowSplit.split()
      • ModelComparison
        • ModelComparison.__init__()
        • ModelComparison.add_result()
        • ModelComparison.compare_metrics()
        • ModelComparison.get_best_model()
      • ModelResult
        • ModelResult.__init__()
        • ModelResult.confidence_intervals
        • ModelResult.forecast
        • ModelResult.metrics
        • ModelResult.model_params
        • ModelResult.name
      • SlidingWindowSplit
        • SlidingWindowSplit.window_size
        • SlidingWindowSplit.step_size
        • SlidingWindowSplit.fh
        • SlidingWindowSplit.__init__()
        • SlidingWindowSplit.split()
      • backtest_forecaster()
      • bias()
      • compare_models()
      • mae()
      • mape()
      • r2_score()
      • rmse()
      • smape()
      • summarize_backtest()
      • ubrmse()
  • Troubleshooting
    • Installation Issues
      • Problem: Import errors for optional dependencies
      • Problem: Python version compatibility
    • Model Fitting Issues
      • Problem: “NotFittedError” when calling predict
      • Problem: “Need at least N data points”
    • Data Validation Issues
      • Problem: “ValidationError” with data types
      • Problem: Data contains NaN or infinite values
    • Serialization Issues
      • Problem: “Failed to save model”
      • Problem: “Failed to load model”
    • Pipeline Issues
      • Problem: Pipeline steps not executing in order
    • Performance Issues
      • Problem: Slow performance with large datasets
    • Logging and Debugging
      • Problem: Too much or too little logging output
      • Problem: Understanding error messages
    • Getting Help
    • Common Error Messages
  • API Stability
    • Versioning Policy
    • Current Version
    • Stable APIs (Post-1.0)
    • Experimental APIs
    • Deprecation Policy
    • Migration Guide
    • Checking Your Version
    • Reporting Issues
TimeSmith
  • Search

© Copyright 2024, Kyle T. Jones.

Built with Sphinx using a theme provided by Read the Docs.