MAterials Simulation Toolkit for Machine Learning (MAST-ML)
  • Acknowledgements
  • MAST-ML version 3.x
    • New changes to MAST-ML
  • Installing MAST-ML
    • Hardware and Data Requirements
      • Hardware
      • Data
    • Terminal installation (Linux or linux-like terminal environment e.g. Mac)
      • Install Python3
        • Create a conda environment (if using Anaconda)
        • Create a virtualenv environment (if not using Anaconda)
      • Install the MAST-ML package via PyPi
      • Install the MAST-ML package via Git
        • Set up Juptyer notebooks
        • Imports that don’t work
    • Windows installation
      • Install Python3
        • Create a conda environment
        • Set up the Spyder IDE and Jupyter notebooks
      • Install the MAST-ML package
        • Imports that don’t work
      • Windows 10 install: step-by-step guide (credit Joe Kern)
  • Getting Started with MAST-ML
    • Installing MAST-ML
    • Performing your first MAST-ML run
  • Overview of MAST-ML tutorials and examples
    • MAST-ML tutorials
  • Code Documentation: Data Cleaning
    • mastml.data_cleaning Module
      • Classes
        • DataCleaning
        • DataUtilities
        • PPCA
      • Class Inheritance Diagram
  • Code Documentation: Data Splitters
    • mastml.data_splitters Module
      • Functions
        • flatten_split_summary
      • Classes
        • BaseSplitter
        • Bootstrap
        • JustEachGroup
        • LeaveCloseCompositionsOut
        • LeaveMultiGroupOut
        • LeaveOutClusterCV
        • LeaveOutPercent
        • LeaveOutTwinCV
        • NoSplit
        • SklearnDataSplitter
      • Class Inheritance Diagram
  • Code Documentation: Datasets
    • mastml.datasets Module
      • Classes
        • FigshareDatasets
        • FoundryDatasets
        • LocalDatasets
        • MatminerDatasets
        • SklearnDatasets
      • Class Inheritance Diagram
  • Code Documentation: Error Analysis
    • mastml.error_analysis Module
      • Classes
        • CorrectionFactors
        • ErrorUtils
      • Class Inheritance Diagram
  • Code Documentation: Feature Generators
    • mastml.feature_generators Module
      • Functions
        • make_composition
      • Classes
        • BaseGenerator
        • CBFVGenerator
        • DataframeUtilities
        • DeepChemFeatureGenerator
        • ElementalFeatureGenerator
        • ElementalFeatureGenerator_Extra
        • ElementalFractionGenerator
        • MaterialsProjectFeatureGenerator
        • MatminerFeatureGenerator
        • OneHotElementGenerator
        • OneHotGroupGenerator
        • PolynomialFeatureGenerator
      • Class Inheritance Diagram
  • Code Documentation: Feature Selectors
    • mastml.feature_selectors Module
      • Functions
        • selected_features_correlation
      • Classes
        • BaseSelector
        • EnsembleModelFeatureSelector
        • MASTMLFeatureSelector
        • NoSelect
        • PearsonSelector
        • ShapFeatureSelector
        • SklearnFeatureSelector
      • Class Inheritance Diagram
  • Code Documentation: Hyperparameter Optimization
    • mastml.hyper_opt Module
      • Classes
        • BayesianSearch
        • GridSearch
        • HyperOptUtils
        • RandomizedSearch
      • Class Inheritance Diagram
  • Code Documentation: Learning Curve
    • mastml.learning_curve Module
      • Classes
        • LearningCurve
      • Class Inheritance Diagram
  • Code Documentation: Mastml
    • mastml.mastml Module
      • Functions
        • parallel
        • write_requirements
      • Classes
        • Mastml
        • NumpyEncoder
      • Class Inheritance Diagram
  • Code Documentation: Metrics
    • mastml.metrics Module
      • Functions
        • r2_score_adjusted
        • r2_score_fitted
        • r2_score_noint
        • rmse_over_stdev
        • root_mean_squared_error
      • Classes
        • Metrics
      • Class Inheritance Diagram
  • Code Documentation: Models
    • mastml.models Module
      • Classes
        • CrabNetModel
        • EnsembleModel
        • HostedModel
        • KANModel
        • SklearnModel
        • SourceNN
        • Transfer
        • model_wrapper
      • Class Inheritance Diagram
  • Code Documentation: Plots
    • mastml.plots Module
      • Functions
        • check_dimensions
        • get_divisor
        • make_axis_same
        • make_fig_ax
        • make_fig_ax_square
        • make_plots
        • nice_mean
        • nice_names
        • nice_range
        • nice_std
        • plot_avg_score_vs_occurrence
        • plot_feature_occurrence
        • plot_stats
        • recursive_max
        • recursive_max_and_min
        • recursive_min
        • reset_index
        • round_down
        • round_up
        • rounder
        • stat_to_string
        • trim_array
      • Classes
        • Classification
        • Error
        • Histogram
        • Line
        • Scatter
      • Class Inheritance Diagram
  • Code Documentation: Preprocessing
    • mastml.preprocessing Module
      • Classes
        • BasePreprocessor
        • MeanStdevScaler
        • NoPreprocessor
        • SklearnPreprocessor
      • Class Inheritance Diagram
  • Code Documentation: Baseline Tests
    • mastml.baseline_tests Module
      • Classes
        • Baseline_tests
      • Class Inheritance Diagram
  • Code Documentation: MAST-ML Predictor
    • mastml.mastml_predictor Module
      • Functions
        • make_prediction
        • make_prediction_dlhub
        • make_prediction_dlhub_OLD
  • Code Documentation: Domain
    • mastml.domain Module
      • Classes
        • Domain
      • Class Inheritance Diagram
MAterials Simulation Toolkit for Machine Learning (MAST-ML)
  • Welcome to MAterials Simulation Toolkit for Machine Learning (MAST-ML)’s documentation!
  • View page source

Welcome to MAterials Simulation Toolkit for Machine Learning (MAST-ML)’s documentation!

  • Acknowledgements
  • MAST-ML version 3.x
    • New changes to MAST-ML
  • Installing MAST-ML
    • Hardware and Data Requirements
    • Terminal installation (Linux or linux-like terminal environment e.g. Mac)
    • Windows installation
  • Getting Started with MAST-ML
    • Installing MAST-ML
    • Performing your first MAST-ML run
  • Overview of MAST-ML tutorials and examples
    • MAST-ML tutorials
  • Code Documentation: Data Cleaning
    • mastml.data_cleaning Module
  • Code Documentation: Data Splitters
    • mastml.data_splitters Module
  • Code Documentation: Datasets
    • mastml.datasets Module
  • Code Documentation: Error Analysis
    • mastml.error_analysis Module
  • Code Documentation: Feature Generators
    • mastml.feature_generators Module
  • Code Documentation: Feature Selectors
    • mastml.feature_selectors Module
  • Code Documentation: Hyperparameter Optimization
    • mastml.hyper_opt Module
  • Code Documentation: Learning Curve
    • mastml.learning_curve Module
  • Code Documentation: Mastml
    • mastml.mastml Module
  • Code Documentation: Metrics
    • mastml.metrics Module
  • Code Documentation: Models
    • mastml.models Module
  • Code Documentation: Plots
    • mastml.plots Module
  • Code Documentation: Preprocessing
    • mastml.preprocessing Module
  • Code Documentation: Baseline Tests
    • mastml.baseline_tests Module
  • Code Documentation: MAST-ML Predictor
    • mastml.mastml_predictor Module
  • Code Documentation: Domain
    • mastml.domain Module

Indices and tables

  • Index

  • Module Index

  • Search Page

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