Documentation of internals

• Documentation of internals
  • Modules
  • Constants
  • Types
  • Functions
  • Macros
  • Index

Modules

# PredictMD.PredictMD — Module.

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# PredictMD.Cleaning — Module.

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# PredictMD.Compilation — Module.

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# PredictMD.GPU — Module.

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# PredictMD.Server — Module.

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Constants

# PredictMD.Fittable — Constant.

Fittable

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Types

# PredictMD.AbstractEstimator — Type.

AbstractEstimator

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# PredictMD.AbstractFeatureContrasts — Type.

AbstractFeatureContrasts

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# PredictMD.AbstractPipeline — Type.

AbstractPipeline

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# PredictMD.AbstractPlot — Type.

AbstractPlot{T}

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# PredictMD.AbstractTransformer — Type.

AbstractTransformer

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# PredictMD.DataFrameFeatureContrasts — Type.

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# PredictMD.DataFrameFeatureContrasts — Method.

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# PredictMD.DecisionTreeModel — Type.

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# PredictMD.GLMModel — Type.

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# PredictMD.ImmutableDataFrame2GLMSingleLabelBinaryClassTransformer — Type.

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# PredictMD.ImmutableFeatureArrayTransposerTransformer — Type.

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# PredictMD.ImmutablePackageMultiLabelPredictionTransformer — Type.

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# PredictMD.ImmutablePackageSingleLabelPredictProbaTransformer — Type.

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# PredictMD.ImmutablePackageSingleLabelPredictionTransformer — Type.

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# PredictMD.ImmutablePredictProbaSingleLabelInt2StringTransformer — Type.

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# PredictMD.ImmutablePredictionsSingleLabelInt2StringTransformer — Type.

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# PredictMD.KnetModel — Type.

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# PredictMD.LIBSVMModel — Type.

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# PredictMD.MutableDataFrame2ClassificationKnetTransformer — Type.

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# PredictMD.MutableDataFrame2DecisionTreeTransformer — Type.

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# PredictMD.MutableDataFrame2RegressionKnetTransformer — Type.

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# PredictMD.SimplePipeline — Type.

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# PredictMD.SimplePipeline — Method.

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Functions

# PredictMD.DataFrame2LIBSVMTransformer — Method.

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# PredictMD._getlabelint2stringmap — Method.

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# PredictMD._getlabelstring2intmap — Method.

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# PredictMD._single_labeldataframeknetregression_Knet — Method.

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# PredictMD._single_labeldataframelinearregression_GLM — Method.

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# PredictMD._single_labeldataframerandomforestregression_DecisionTree — Method.

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# PredictMD._single_labeldataframesvmregression_LIBSVM — Method.

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# PredictMD._single_labelmulticlassdataframeknetclassifier_Knet — Method.

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# PredictMD._single_labelmulticlassdataframesvmclassifier_LIBSVM — Method.

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# PredictMD._single_labelmulticlassdfrandomforestclassifier_DecisionTree — Method.

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# PredictMD._singlelabelbinaryclassdataframelogisticclassifier_GLM — Method.

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# PredictMD._singlelabelbinaryclassdataframeprobitclassifier_GLM — Method.

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# PredictMD._singlelabelbinaryclassificationmetrics — Method.

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# PredictMD._singlelabelbinaryclassificationmetrics_tunableparam — Method.

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# PredictMD._singlelabelregressionmetrics — Method.

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# PredictMD.accuracy — Method.

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# PredictMD.auprc — Method.

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# PredictMD.aurocc — Method.

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# PredictMD.averageprecisionscore — Method.

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# PredictMD.avg_precision — Method.

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# PredictMD.binary_brier_score — Method.

binary_brier_score(ytrue, yscore)

Computes the binary formulation of the Brier score, defined as:

$$\frac{1}{N}\sum\limits _{t=1}^{N}(f_t-o_t)^2 \,\!$$

Lower values are better. Best value is 0.

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# PredictMD.calculate_smote_pct_under — Method.

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# PredictMD.check_column_types — Method.

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# PredictMD.cohen_kappa — Method.

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# PredictMD.cohen_kappa — Method.

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# PredictMD.cohen_kappa — Method.

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# PredictMD.compute_contingency_table — Method.

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# PredictMD.compute_contingency_table — Method.

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# PredictMD.convert_value_to_missing! — Function.

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# PredictMD.delete_nothings! — Method.

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# PredictMD.f1score — Method.

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# PredictMD.false_negative_rate — Method.

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# PredictMD.false_positive_rate — Method.

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# PredictMD.fbetascore — Method.

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# PredictMD.filename_extension — Method.

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# PredictMD.fit! — Function.

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# PredictMD.fit! — Function.

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# PredictMD.fit! — Function.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fit! — Method.

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# PredictMD.fix_column_types! — Method.

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# PredictMD.fix_type — Function.

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# PredictMD.generate_feature_contrasts — Method.

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# PredictMD.generate_formula — Method.

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# PredictMD.generate_formula — Method.

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# PredictMD.generate_formula — Method.

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# PredictMD.generate_formula — Method.

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# PredictMD.generate_interaction_terms — Method.

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# PredictMD.get_binary_thresholds — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_history — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.get_underlying — Method.

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# PredictMD.getallrocnums — Method.

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# PredictMD.icd9_code_to_single_level_dx_ccs — Method.

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# PredictMD.inverse — Method.

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# PredictMD.is_appveyor_ci — Function.

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# PredictMD.is_ci — Function.

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# PredictMD.is_ci_or_runtests — Function.

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# PredictMD.is_ci_or_runtests_or_docs_or_examples — Function.

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# PredictMD.is_deploy_docs — Function.

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# PredictMD.is_docs_or_examples — Function.

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# PredictMD.is_make_docs — Function.

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# PredictMD.is_make_examples — Function.

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# PredictMD.is_nothing — Function.

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# PredictMD.is_one_to_one — Method.

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# PredictMD.is_runtests — Function.

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# PredictMD.is_square — Method.

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# PredictMD.is_travis_ci — Function.

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# PredictMD.is_travis_ci_on_apple — Function.

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# PredictMD.is_travis_ci_on_linux — Function.

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# PredictMD.load_model — Method.

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# PredictMD.mean_square_error — Method.

mean_square_error(ytrue, ypred)

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# PredictMD.multilabelprobabilitiestopredictions — Method.

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# PredictMD.negative_predictive_value — Method.

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# PredictMD.open_plots_during_tests — Function.

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# PredictMD.package_directory — Method.

package_directory(parts...)::String

Equivalent to abspath(joinpath(abspath(package_directory()), parts...)).

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# PredictMD.package_directory — Method.

package_directory(f::Function, types::Tuple)::String

If function f with type signature types is part of a Julia package, returns the package root directory.

If function f with type signature types is not part of a Julia package, throws an error.

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# PredictMD.package_directory — Method.

package_directory(f::Function)::String

If function f is part of a Julia package, returns the package root directory.

If function f is not part of a Julia package, throws an error.

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# PredictMD.package_directory — Method.

package_directory(m::Method)::String

If method m is part of a Julia package, returns the package root directory.

If method m is not part of a Julia package, throws an error.

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# PredictMD.package_directory — Method.

package_directory(m::Module, parts...)::String

Equivalent to result = abspath(joinpath(abspath(package_directory(m)), parts...)).

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# PredictMD.package_directory — Method.

package_directory(m::Module)::String

If module m is part of a Julia package, returns the package root directory.

If module m is not part of a Julia package, throws an error.

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# PredictMD.package_directory — Method.

package_directory()::String

Return the PredictMD package directory.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.parse_functions! — Method.

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# PredictMD.plot_probability_calibration_curve — Method.

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# PredictMD.plot_probability_calibration_curve — Method.

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# PredictMD.plotlearningcurves — Function.

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# PredictMD.plotlearningcurves — Function.

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# PredictMD.plotlearningcurves — Method.

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# PredictMD.plotprcurves — Method.

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# PredictMD.plotprcurves — Method.

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# PredictMD.plotroccurves — Method.

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# PredictMD.plotroccurves — Method.

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# PredictMD.plotsinglelabelbinaryclassifierhistogram — Method.

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# PredictMD.plotsinglelabelregressiontrueversuspredicted — Method.

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# PredictMD.positive_predictive_value — Method.

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# PredictMD.prcurve — Method.

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# PredictMD.prcurve — Method.

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# PredictMD.precision — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predict_proba — Method.

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# PredictMD.predictionsassoctodataframe — Function.

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# PredictMD.probability_calibration_metrics — Function.

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# PredictMD.probability_calibration_metrics — Method.

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# PredictMD.probability_calibration_scores_and_fractions — Method.

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# PredictMD.probability_calibration_scores_and_fractions — Method.

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# PredictMD.r2_score — Method.

r2_score(ytrue, ypred)

Computes coefficient of determination. Higher values are better. Best value is 1.

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# PredictMD.recall — Method.

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# PredictMD.risk_score_cutoff_values — Method.

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# PredictMD.risk_score_cutoff_values — Method.

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# PredictMD.roccurve — Method.

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# PredictMD.roccurve — Method.

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# PredictMD.root_mean_square_error — Method.

root_mean_square_error(ytrue, ypred)

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# PredictMD.save_model — Method.

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# PredictMD.sensitivity — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_feature_contrasts! — Method.

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# PredictMD.set_max_epochs! — Method.

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# PredictMD.set_max_epochs! — Method.

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# PredictMD.set_max_epochs! — Method.

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# PredictMD.shuffle_rows! — Method.

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# PredictMD.shuffle_rows! — Method.

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# PredictMD.simple_linear_regression — Method.

simple_linear_regression(x::AbstractVector, y::AbstractVector)

Simple linear regression - given a set of two-dimensional points (x, y), use the ordinary least squares method to find the best fit line of the form y = a + b*x (where a and b are real numbers) and return the tuple (a, b).

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# PredictMD.simple_moving_average — Method.

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# PredictMD.single_labeldataframeknetregression — Method.

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# PredictMD.single_labeldataframelinearregression — Method.

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# PredictMD.single_labeldataframerandomforestregression — Method.

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# PredictMD.single_labeldataframesvmregression — Method.

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# PredictMD.single_labelmulticlassdataframeknetclassifier — Method.

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# PredictMD.single_labelmulticlassdataframerandomforestclassifier — Method.

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# PredictMD.single_labelmulticlassdataframesvmclassifier — Method.

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# PredictMD.single_labelprobabilitiestopredictions — Method.

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# PredictMD.singlelabelbinaryclassdataframelogisticclassifier — Method.

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# PredictMD.singlelabelbinaryclassdataframeprobitclassifier — Method.

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# PredictMD.singlelabelbinaryclassificationmetrics — Method.

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# PredictMD.singlelabelbinaryclassificationmetrics — Method.

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# PredictMD.singlelabelbinaryyscore — Method.

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# PredictMD.singlelabelbinaryytrue — Method.

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# PredictMD.singlelabelregressionmetrics — Method.

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# PredictMD.singlelabelregressionmetrics — Method.

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# PredictMD.singlelabelregressionypred — Method.

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# PredictMD.singlelabelregressionytrue — Method.

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# PredictMD.smote — Method.

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# PredictMD.smote — Method.

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# PredictMD.specificity — Method.

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# PredictMD.split_data — Method.

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# PredictMD.split_data — Method.

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# PredictMD.transform — Function.

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# PredictMD.transform — Function.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform — Method.

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# PredictMD.transform_columns! — Function.

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# PredictMD.trapz — Method.

trapz(x, y)

Compute the area under the curve of 2-dimensional points (x, y) using the trapezoidal method.

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# PredictMD.true_negative_rate — Method.

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# PredictMD.true_positive_rate — Method.

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# PredictMD.tuplify — Function.

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# PredictMD.underlying — Method.

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# PredictMD.version — Method.

version(f::Function, types::Tuple)::VersionNumber

If function f with type signature types is part of a Julia package, returns the version number of that package.

If function f with type signature types is not part of a Julia package, throws an error.

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# PredictMD.version — Method.

version(f::Function)::VersionNumber

If function f is part of a Julia package, returns the version number of that package.

If function f is not part of a Julia package, throws an error.

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# PredictMD.version — Method.

version(m::Method)::VersionNumber

If method m is part of a Julia package, returns the version number of that package.

If method m is not part of a Julia package, throws an error.

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# PredictMD.version — Method.

version(m::Module)::VersionNumber

If module m is part of a Julia package, returns the version number of that package.

If module m is not part of a Julia package, throws an error.

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# PredictMD.version — Method.

version()::VersionNumber

Return the version number of PredictMD.

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# PredictMD.Cleaning.ccs_onehot_names — Function.

Given a dataframe, return the column names corresponding to CCS "one-hot" columns.

Examples

import CSVFiles
import FileIO
import PredictMD

df = DataFrames.DataFrame(
    FileIO.load(
        MY_CSV_FILE_NAME;
        type_detect_rows = 30_000,
        )
    )

@info(PredictMD.Cleaning.ccs_onehot_names(df))
@info(PredictMD.Cleaning.ccs_onehot_names(df, "ccs_onehot_"))

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# PredictMD.Cleaning.clean_hcup_nis_csv_icd9 — Method.

Given a single ICD 9 code, import the relevant patients from the Health Care Utilization Project (HCUP) National Inpatient Sample (NIS) database.

Examples:

import CSVFiles
import FileIO
import PredictMD

icd_code_list = ["8841"]
icd_code_type=:procedure
input_file_name_list = [
    "./data/nis_2012_core.csv",
    "./data/nis_2013_core.csv",
    "./data/nis_2014_core.csv",
    ]
output_file_name = "./output/hcup_nis_pr_8841.csv"

PredictMD.Cleaning.clean_hcup_nis_csv_icd9(
    icd_code_list,
    input_file_name_list,
    output_file_name;
    icd_code_type=icd_code_type,
    rows_for_type_detect = 30_000,
    )

df = DataFrames.DataFrame(
    FileIO.load(
        output_file_name;
        type_detect_rows = 30_000,
        )
    )

@info(PredictMD.Cleaning.ccs_onehot_names(df))

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# PredictMD.Cleaning.column_names_with_prefix — Method.

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# PredictMD.Cleaning.symbol_begins_with — Method.

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# PredictMD.Cleaning.x_contains_y — Method.

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Macros

Index

• PredictMD.Cleaning
• PredictMD.Compilation
• PredictMD.GPU
• PredictMD.PredictMD
• PredictMD.Server
• PredictMD.Fittable
• PredictMD.AbstractEstimator
• PredictMD.AbstractFeatureContrasts
• PredictMD.AbstractPipeline
• PredictMD.AbstractPlot
• PredictMD.AbstractTransformer
• PredictMD.DataFrameFeatureContrasts
• PredictMD.DataFrameFeatureContrasts
• PredictMD.DecisionTreeModel
• PredictMD.GLMModel
• PredictMD.ImmutableDataFrame2GLMSingleLabelBinaryClassTransformer
• PredictMD.ImmutableFeatureArrayTransposerTransformer
• PredictMD.ImmutablePackageMultiLabelPredictionTransformer
• PredictMD.ImmutablePackageSingleLabelPredictProbaTransformer
• PredictMD.ImmutablePackageSingleLabelPredictionTransformer
• PredictMD.ImmutablePredictProbaSingleLabelInt2StringTransformer
• PredictMD.ImmutablePredictionsSingleLabelInt2StringTransformer
• PredictMD.KnetModel
• PredictMD.LIBSVMModel
• PredictMD.MutableDataFrame2ClassificationKnetTransformer
• PredictMD.MutableDataFrame2DecisionTreeTransformer
• PredictMD.MutableDataFrame2RegressionKnetTransformer
• PredictMD.SimplePipeline
• PredictMD.SimplePipeline
• PredictMD.Cleaning.ccs_onehot_names
• PredictMD.Cleaning.clean_hcup_nis_csv_icd9
• PredictMD.Cleaning.column_names_with_prefix
• PredictMD.Cleaning.symbol_begins_with
• PredictMD.Cleaning.x_contains_y
• PredictMD.DataFrame2LIBSVMTransformer
• PredictMD._getlabelint2stringmap
• PredictMD._getlabelstring2intmap
• PredictMD._single_labeldataframeknetregression_Knet
• PredictMD._single_labeldataframelinearregression_GLM
• PredictMD._single_labeldataframerandomforestregression_DecisionTree
• PredictMD._single_labeldataframesvmregression_LIBSVM
• PredictMD._single_labelmulticlassdataframeknetclassifier_Knet
• PredictMD._single_labelmulticlassdataframesvmclassifier_LIBSVM
• PredictMD._single_labelmulticlassdfrandomforestclassifier_DecisionTree
• PredictMD._singlelabelbinaryclassdataframelogisticclassifier_GLM
• PredictMD._singlelabelbinaryclassdataframeprobitclassifier_GLM
• PredictMD._singlelabelbinaryclassificationmetrics
• PredictMD._singlelabelbinaryclassificationmetrics_tunableparam
• PredictMD._singlelabelregressionmetrics
• PredictMD.accuracy
• PredictMD.auprc
• PredictMD.aurocc
• PredictMD.averageprecisionscore
• PredictMD.avg_precision
• PredictMD.binary_brier_score
• PredictMD.calculate_smote_pct_under
• PredictMD.check_column_types
• PredictMD.cohen_kappa
• PredictMD.cohen_kappa
• PredictMD.cohen_kappa
• PredictMD.compute_contingency_table
• PredictMD.compute_contingency_table
• PredictMD.convert_value_to_missing!
• PredictMD.delete_nothings!
• PredictMD.f1score
• PredictMD.false_negative_rate
• PredictMD.false_positive_rate
• PredictMD.fbetascore
• PredictMD.filename_extension
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fit!
• PredictMD.fix_column_types!
• PredictMD.fix_type
• PredictMD.generate_feature_contrasts
• PredictMD.generate_formula
• PredictMD.generate_formula
• PredictMD.generate_formula
• PredictMD.generate_formula
• PredictMD.generate_interaction_terms
• PredictMD.get_binary_thresholds
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_history
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.get_underlying
• PredictMD.getallrocnums
• PredictMD.icd9_code_to_single_level_dx_ccs
• PredictMD.inverse
• PredictMD.is_appveyor_ci
• PredictMD.is_ci
• PredictMD.is_ci_or_runtests
• PredictMD.is_ci_or_runtests_or_docs_or_examples
• PredictMD.is_deploy_docs
• PredictMD.is_docs_or_examples
• PredictMD.is_make_docs
• PredictMD.is_make_examples
• PredictMD.is_nothing
• PredictMD.is_one_to_one
• PredictMD.is_runtests
• PredictMD.is_square
• PredictMD.is_travis_ci
• PredictMD.is_travis_ci_on_apple
• PredictMD.is_travis_ci_on_linux
• PredictMD.load_model
• PredictMD.mean_square_error
• PredictMD.multilabelprobabilitiestopredictions
• PredictMD.negative_predictive_value
• PredictMD.open_plots_during_tests
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.package_directory
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.parse_functions!
• PredictMD.plot_probability_calibration_curve
• PredictMD.plot_probability_calibration_curve
• PredictMD.plotlearningcurves
• PredictMD.plotlearningcurves
• PredictMD.plotlearningcurves
• PredictMD.plotprcurves
• PredictMD.plotprcurves
• PredictMD.plotroccurves
• PredictMD.plotroccurves
• PredictMD.plotsinglelabelbinaryclassifierhistogram
• PredictMD.plotsinglelabelregressiontrueversuspredicted
• PredictMD.positive_predictive_value
• PredictMD.prcurve
• PredictMD.prcurve
• PredictMD.precision
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predict_proba
• PredictMD.predictionsassoctodataframe
• PredictMD.probability_calibration_metrics
• PredictMD.probability_calibration_metrics
• PredictMD.probability_calibration_scores_and_fractions
• PredictMD.probability_calibration_scores_and_fractions
• PredictMD.r2_score
• PredictMD.recall
• PredictMD.risk_score_cutoff_values
• PredictMD.risk_score_cutoff_values
• PredictMD.roccurve
• PredictMD.roccurve
• PredictMD.root_mean_square_error
• PredictMD.save_model
• PredictMD.sensitivity
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_feature_contrasts!
• PredictMD.set_max_epochs!
• PredictMD.set_max_epochs!
• PredictMD.set_max_epochs!
• PredictMD.shuffle_rows!
• PredictMD.shuffle_rows!
• PredictMD.simple_linear_regression
• PredictMD.simple_moving_average
• PredictMD.single_labeldataframeknetregression
• PredictMD.single_labeldataframelinearregression
• PredictMD.single_labeldataframerandomforestregression
• PredictMD.single_labeldataframesvmregression
• PredictMD.single_labelmulticlassdataframeknetclassifier
• PredictMD.single_labelmulticlassdataframerandomforestclassifier
• PredictMD.single_labelmulticlassdataframesvmclassifier
• PredictMD.single_labelprobabilitiestopredictions
• PredictMD.singlelabelbinaryclassdataframelogisticclassifier
• PredictMD.singlelabelbinaryclassdataframeprobitclassifier
• PredictMD.singlelabelbinaryclassificationmetrics
• PredictMD.singlelabelbinaryclassificationmetrics
• PredictMD.singlelabelbinaryyscore
• PredictMD.singlelabelbinaryytrue
• PredictMD.singlelabelregressionmetrics
• PredictMD.singlelabelregressionmetrics
• PredictMD.singlelabelregressionypred
• PredictMD.singlelabelregressionytrue
• PredictMD.smote
• PredictMD.smote
• PredictMD.specificity
• PredictMD.split_data
• PredictMD.split_data
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform
• PredictMD.transform_columns!
• PredictMD.trapz
• PredictMD.true_negative_rate
• PredictMD.true_positive_rate
• PredictMD.tuplify
• PredictMD.underlying
• PredictMD.version
• PredictMD.version
• PredictMD.version
• PredictMD.version
• PredictMD.version