Function reference • pdstools

All functions
`ADMDatamart()`	Generic method to read ADM Datamart data.
`adm2pmml()`	Generates PMML files from ADM models.
`admJSONFactoryToBinning()`	Turns an ADM Factory JSON into an easy-to-process binning table.
`admVarImp()`	Calculate variable importance from ADM Datamart data.
`adm_datamart`	Sample ADM Data Mart model and predictor data.
`auc2GINI()`	Convert AUC performance metric to GINI.
`auc_from_bincounts()`	Calculates AUC from counts of positives and negatives directly.
`auc_from_probs()`	Calculates AUC from an array of truth values and predictions.
`aucpr_from_bincounts()`	Calculates PR AUC (precision-recall) from counts of positives and negatives directly.
`aucpr_from_probs()`	Calculates PR AUC (precision-recall) from an array of truth values and predictions.
`defaultPredictorCategorization()`	Default predictor categorization. Return a category label given a predictor name.
`filterActiveOnly()`	Subset the datamart predictor data to only the active predictors.
`filterClassifierOnly()`	Subset the datamart predictor data to only the classifier binning.
`filterInactiveOnly()`	Subset the datamart predictor data to only the inactive predictors.
`filterLatestSnapshotOnly()`	Subset the provided datamart data to just the latest snapshot per model.
`filterPredictorBinning()`	Remove the binning information from the provided datamart predictor data so it only is predictor level, not more detailed. This is commonly used in plotting functions.
`fromPRPCDateTime()`	Convert from a Pega date-time string.
`getActiveRanges()`	Get the active (reachable) score range of one or more models.
`getJSONModelContextAsString()`	Converts a model partition (context) from a JSON representation to a string
`getModelsFromJSONTable()`	Retrieves ADM models from the internal "Factory" table.
`getScorecardFromSnapshot()`	Convert a model snapshot into a human-readable as well as machine-executable PMML Scorecard.
`getScoringModelFromJSONFactoryString()`	Create a human-readable as well as machine-executable Scorecard from the JSON of a specific model.
`hasMultipleSnapshots()`	Check if data has multiple snapshots
`hds`	A sample export of a Historical Dataset to illustrate how to import and analyze this.
`ihsampledata`	A small sample of IH data to illustrate how to import and analyze this.
`lift()`	Calculates lift from counts of positives and negatives.
`pdstools`	pdstools: Open-sourced Data Science tools for Pega.
`plotBinning()`	Create binning plot for any predictor.
`plotBinningLift()`	Create an alternative binning plot for any predictor.
`plotCumulativeGains()`	Create cum gains plot for the model classifier.
`plotCumulativeLift()`	Create cum lift plot for the model classifier.
`plotPerformanceOverTime()`	Plot ADM Model Performance over time
`plotPerformanceSuccessRateBoxPlot()`	Create box plot of performance x success rate from ADM datamart model data.
`plotPerformanceSuccessRateBubbleChart()`	Create bubble chart from ADM datamart model data.
`plotPredictorImportance()`	Create boxplots per predictor with performance range in models.
`plotPredictorImportanceHeatmap()`	Performance of predictors per proposition
`plotPropositionSuccessRates()`	Plot ADM Proposition Success Rates
`plotSuccessRateOverTime()`	Plot ADM Model Success Rate over time
`printADMPredictorInfo()`	HTML snippet with predictor info.
`readDSExport()`	Read a Pega dataset export file.
`reasonCodesAboveMean()`	PMML Scorecard Reason code specification
`reasonCodesAboveMin()`	PMML Scorecard Reason code specification
`reasonCodesBelowMax()`	PMML Scorecard Reason code specification
`reasonCodesBelowMean()`	PMML Scorecard Reason code specification
`standardizeFieldCasing()`	Fix field casing
`toPRPCDateTime()`	Convert to a Pega date-time string.
`userFriendlyADMBinning()`	Creates user friendly table with binning info.
`writeDSExport()`	Write table to a file in the format of the dataset export files.
`zratio()`	Calculates the Z-Ratio for the success rate from counts of positives and negatives.

Reference

All functions