diff --git a/README.md b/README.md index e93d523..693a363 100644 --- a/README.md +++ b/README.md @@ -25,6 +25,8 @@ Java library and command-line application for converting [R](https://www.r-proje * [`adabag`](https://cran.r-project.org/package=adabag) package: * `bagging` - Bagging classification * `boosting` - Boosting classification + * [`apollo`](https://cran.r-project.org/package=apollo) + * `maxLik`- Discrete Choice Model (DCM) classification * [`caret`](https://cran.r-project.org/package=caret) package: * `preProcess` - Transformation methods "range", "center", "scale" and "medianImpute" * `train` - Selected JPMML-R model types diff --git a/pmml-rexp/src/main/java/org/jpmml/rexp/MaxLikConverter.java b/pmml-rexp/src/main/java/org/jpmml/rexp/MaxLikConverter.java new file mode 100644 index 0000000..3af9930 --- /dev/null +++ b/pmml-rexp/src/main/java/org/jpmml/rexp/MaxLikConverter.java @@ -0,0 +1,238 @@ +/* + * Copyright (c) 2024 Villu Ruusmann + * + * This file is part of JPMML-R + * + * JPMML-R is free software: you can redistribute it and/or modify + * it under the terms of the GNU Affero General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * JPMML-R is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU Affero General Public License for more details. + * + * You should have received a copy of the GNU Affero General Public License + * along with JPMML-R. If not, see . + */ +package org.jpmml.rexp; + +import java.util.ArrayList; +import java.util.Collections; +import java.util.Iterator; +import java.util.LinkedHashMap; +import java.util.List; +import java.util.Map; +import java.util.Objects; + +import org.dmg.pmml.DataField; +import org.dmg.pmml.DataType; +import org.dmg.pmml.DerivedField; +import org.dmg.pmml.Expression; +import org.dmg.pmml.FieldRef; +import org.dmg.pmml.MiningFunction; +import org.dmg.pmml.OpType; +import org.dmg.pmml.regression.RegressionModel; +import org.dmg.pmml.regression.RegressionTable; +import org.jpmml.converter.CategoricalLabel; +import org.jpmml.converter.ContinuousFeature; +import org.jpmml.converter.ExpressionUtil; +import org.jpmml.converter.Feature; +import org.jpmml.converter.FieldNameUtil; +import org.jpmml.converter.ModelUtil; +import org.jpmml.converter.Schema; +import org.jpmml.converter.TypeUtil; +import org.jpmml.converter.regression.RegressionModelUtil; + +public class MaxLikConverter extends ModelConverter { + + public MaxLikConverter(RGenericVector maxLik){ + super(maxLik); + } + + @Override + public void encodeSchema(RExpEncoder encoder){ + RGenericVector maxLik = getObject(); + + RDoubleVector estimate = maxLik.getDoubleElement("estimate"); + RClosure apolloProbabilities = (RClosure)maxLik.getElement("apollo_probabilities"); + + RStringVector estimateNames = estimate.names(); + + Map betas = new LinkedHashMap<>(); + + for(int i = 0; i < estimate.size(); i++){ + betas.put(estimateNames.getDequotedValue(i), estimate.getValue(i)); + } + + RFunctionCall body = (RFunctionCall)apolloProbabilities.getBody(); + + if(!body.hasValue("{")){ + throw new IllegalArgumentException(); + } + + Map utilityFunctions = new LinkedHashMap<>(); + + for(Iterator it = body.argumentValues(); it.hasNext(); ){ + RExp argValue = it.next(); + + if(argValue instanceof RFunctionCall){ + RFunctionCall functionCall = (RFunctionCall)argValue; + + if(functionCall.hasValue("=")){ + Iterator it2 = functionCall.argumentValues(); + + RExp firstArgValue = it2.next(); + RExp secondArgValue = it2.next(); + + Object choice = matchUtilityFunction(firstArgValue); + if(choice != null){ + utilityFunctions.put(choice, secondArgValue); + } + } + } else + + { + throw new IllegalArgumentException(); + } + } + + if(utilityFunctions.isEmpty()){ + throw new IllegalArgumentException(); + } + + List choices = new ArrayList<>(utilityFunctions.keySet()); + + DataField choiceField = encoder.createDataField("choice", OpType.CATEGORICAL, TypeUtil.getDataType(choices, DataType.STRING), choices); + + encoder.setLabel(choiceField); + + for(Object choice : choices){ + RFunctionCall functionCall = (RFunctionCall)utilityFunctions.get(choice); + + Expression expression = toPMML(functionCall, betas, encoder); + + DerivedField derivedField = encoder.createDerivedField(FieldNameUtil.create("utility", choice), OpType.CONTINUOUS, DataType.DOUBLE, expression); + + Feature feature = new ContinuousFeature(encoder, derivedField); + + encoder.addFeature(feature); + } + } + + @Override + public RegressionModel encodeModel(Schema schema){ + RGenericVector maxLik = getObject(); + + CategoricalLabel categoricalLabel = (CategoricalLabel)schema.getLabel(); + List features = schema.getFeatures(); + + List regressionTables = new ArrayList<>(); + + for(int i = 0; i < categoricalLabel.size(); i++){ + Feature feature = features.get(i); + + RegressionTable regressionTable = RegressionModelUtil.createRegressionTable(Collections.singletonList(feature), Collections.singletonList(1d), null) + .setTargetCategory(categoricalLabel.getValue(i)); + + regressionTables.add(regressionTable); + } + + RegressionModel regressionModel = new RegressionModel(MiningFunction.CLASSIFICATION, ModelUtil.createMiningSchema(categoricalLabel), regressionTables) + .setNormalizationMethod(RegressionModel.NormalizationMethod.SOFTMAX) + .setOutput(ModelUtil.createProbabilityOutput(DataType.DOUBLE, categoricalLabel)); + + return regressionModel; + } + + static + private Object matchUtilityFunction(RExp argValue){ + + if(argValue instanceof RFunctionCall){ + RFunctionCall functionCall = (RFunctionCall)argValue; + + if(functionCall.hasValue("[[")){ + Iterator it = functionCall.argumentValues(); + + RExp firstArgValue = it.next(); + + if(firstArgValue instanceof RString){ + RString string = (RString)firstArgValue; + + if(Objects.equals("V", string.getValue())){ + RExp secondArgValue = it.next(); + + if(secondArgValue instanceof RVector){ + RVector vector = (RVector)secondArgValue; + + return vector.asScalar(); + } + } + } + } + } + + return null; + } + + static + private Expression toPMML(RExp argumentValue, Map betas, RExpEncoder encoder){ + + if(argumentValue instanceof RString){ + RString string = (RString)argumentValue; + + String stringValue = string.getValue(); + if(betas.containsKey(stringValue)){ + return ExpressionUtil.createConstant(betas.get(stringValue)); + } + + DataField dataField = encoder.getDataField(stringValue); + if(dataField == null){ + dataField = encoder.createDataField(stringValue, OpType.CONTINUOUS, DataType.DOUBLE); + } + + return new FieldRef(stringValue); + } else + + if(argumentValue instanceof RNumberVector){ + RNumberVector numberVector = (RNumberVector)argumentValue; + + return ExpressionUtil.createConstant(numberVector.asScalar()); + } else + + if(argumentValue instanceof RFunctionCall){ + RFunctionCall functionCall = (RFunctionCall)argumentValue; + + RString value = (RString)functionCall.getValue(); + Iterator it = functionCall.argumentValues(); + + try { + switch(value.getValue()){ + case "(": + return toPMML(it.next(), betas, encoder); + case "+": + case "-": + case "*": + case "/": + // XXX + return ExpressionUtil.createApply(value.getValue(), + toPMML(it.next(), betas, encoder), + toPMML(it.next(), betas, encoder) + ); + default: + throw new IllegalArgumentException(value.getValue()); + } + } finally { + + if(it.hasNext()){ + throw new IllegalStateException(); + } + } + } else + + { + throw new IllegalArgumentException(); + } + } +} \ No newline at end of file diff --git a/pmml-rexp/src/main/java/org/jpmml/rexp/RFunctionCall.java b/pmml-rexp/src/main/java/org/jpmml/rexp/RFunctionCall.java index 35a6bb7..908aa33 100644 --- a/pmml-rexp/src/main/java/org/jpmml/rexp/RFunctionCall.java +++ b/pmml-rexp/src/main/java/org/jpmml/rexp/RFunctionCall.java @@ -18,19 +18,113 @@ */ package org.jpmml.rexp; +import java.util.Iterator; +import java.util.NoSuchElementException; +import java.util.Objects; + public class RFunctionCall extends RPair { - public RFunctionCall(RExp tag, RExp function, RPair arguments, RPair attributes){ - super(tag, function, attributes); + public RFunctionCall(RExp tag, RExp value, RPair arguments, RPair attributes){ + super(tag, value, attributes); setNext(arguments); } - public RExp getFunction(){ - return getValue(); + public boolean hasValue(String string){ + RString value = (RString)getValue(); + + return Objects.equals(string, value.getValue()); } - public RPair getArguments(){ - return getNext(); + public Iterator arguments(){ + Iterator result = new Iterator(){ + + private RPair next = getNext(); + + + @Override + public boolean hasNext(){ + return (this.next != null); + } + + @Override + public RPair next(){ + RPair result = this.next; + + if(result == null){ + throw new NoSuchElementException(); + } + + this.next = result.getNext(); + + return result; + } + }; + + return result; + } + + public Iterator argumentValues(){ + Iterator result = new Iterator(){ + + private Iterator argumentIt = arguments(); + + + @Override + public boolean hasNext(){ + return this.argumentIt.hasNext(); + } + + @Override + public RExp next(){ + RPair argument = this.argumentIt.next(); + + return argument.getValue(); + } + }; + + return result; + } + + public String toTreeString(String indent){ + StringBuilder sb = new StringBuilder(); + + // Operator + RString value = (RString)getValue(); + + sb.append(indent).append(value.getValue()); + + indent += "\t"; + + // Operands + for(Iterator it = argumentValues(); it.hasNext(); ){ + RExp argValue = it.next(); + + sb.append("\n"); + + if(argValue instanceof RString){ + RString string = (RString)argValue; + + sb.append(indent).append(string.getValue()).append(" // ").append(argValue.getClass().getSimpleName()); + } else + + if(argValue instanceof RVector){ + RVector vector = (RVector)argValue; + + sb.append(indent).append(vector.asScalar()).append(" // ").append(argValue.getClass().getSimpleName()); + } else + + if(argValue instanceof RFunctionCall){ + RFunctionCall functionCall = (RFunctionCall)argValue; + + sb.append(functionCall.toTreeString(indent)); + } else + + { + throw new IllegalArgumentException(argValue.getClass().getName()); + } + } + + return sb.toString(); } } \ No newline at end of file diff --git a/pmml-rexp/src/main/resources/META-INF/r2pmml.properties b/pmml-rexp/src/main/resources/META-INF/r2pmml.properties index eeb28a3..5c508d0 100644 --- a/pmml-rexp/src/main/resources/META-INF/r2pmml.properties +++ b/pmml-rexp/src/main/resources/META-INF/r2pmml.properties @@ -15,6 +15,7 @@ kmeans = org.jpmml.rexp.KMeansConverter lm = org.jpmml.rexp.LMConverter lognet = org.jpmml.rexp.LogNetConverter lrm = org.jpmml.rexp.LRMConverter +maxLik = org.jpmml.rexp.MaxLikConverter multinom = org.jpmml.rexp.MultinomConverter multnet = org.jpmml.rexp.MultNetConverter mvr = org.jpmml.rexp.MVRConverter diff --git a/pmml-rexp/src/test/R/apollo.R b/pmml-rexp/src/test/R/apollo.R new file mode 100644 index 0000000..a2023a3 --- /dev/null +++ b/pmml-rexp/src/test/R/apollo.R @@ -0,0 +1,89 @@ +library("apollo") + +source("util.R") + +apollo_initialise() + +# See http://www.apollochoicemodelling.com/files/examples/1%20MNL/MNL_RP.r +generateMNLModeChoice = function(){ + database <<- loadModeChoiceCsv("ModeChoice") + + apollo_control <<- list( + modelName = "MNL_RP", + modelDescr = "Simple MNL model on mode choice RP data", + indivID = "ID", + outputDirectory = "/dev/null" + ) + + apollo_beta <<- c( + asc_car = 0, + asc_bus = 0, + asc_air = 0, + asc_rail = 0, + b_tt_car = 0, + b_tt_bus = 0, + b_tt_air = 0, + b_tt_rail = 0, + b_access = 0, + b_cost = 0 + ) + + apollo_fixed <<- c("asc_car") + + apollo_inputs = apollo_validateInputs() + + apollo_probabilities = function(apollo_beta, apollo_inputs, functionality="estimate"){ + + ### Attach inputs and detach after function exit + apollo_attach(apollo_beta, apollo_inputs) + on.exit(apollo_detach(apollo_beta, apollo_inputs)) + + ### Create list of probabilities P + P = list() + + ### List of utilities: these must use the same names as in mnl_settings, order is irrelevant + V = list() + V[["car"]] = asc_car + b_tt_car * time_car + b_cost * cost_car + V[["bus"]] = asc_bus + b_tt_bus * time_bus + b_access * access_bus + b_cost * cost_bus + V[["air"]] = asc_air + b_tt_air * time_air + b_access * access_air + b_cost * cost_air + V[["rail"]] = asc_rail + b_tt_rail * time_rail + b_access * access_rail + b_cost * cost_rail + + ### Define settings for MNL model component + mnl_settings = list( + alternatives = c(car=1, bus=2, air=3, rail=4), + #avail = list(car=av_car, bus=av_bus, air=av_air, rail=av_rail), + choiceVar = choice, + utilities = V + ) + + ### Compute probabilities using MNL model + P[["model"]] = apollo_mnl(mnl_settings, functionality) + + ### Take product across observation for same individual + P = apollo_panelProd(P, apollo_inputs, functionality) + + ### Prepare and return outputs of function + P = apollo_prepareProb(P, apollo_inputs, functionality) + + return(P) + } + + model = apollo_estimate(apollo_beta, apollo_fixed, apollo_probabilities, apollo_inputs) + print(model) + + choices = c("car", "bus", "air", "rail") + + choice = apollo_prediction(model, apollo_probabilities, apollo_inputs) + choice = choice[choices] + colnames(choice) = lapply(choices, function(x){ paste("probability(", x, ")", sep = "")}) + choice$choice = apply(choice, 1, function(x) { choices[which.max(x)] }) + + storeRds(model, "MNLModeChoice") + storeCsv(choice, "MNLModeChoice") +} + +set.seed(42) + +rm(list = c("database", "apollo_control", "apollo_beta", "apollo_fixed")) + +generateMNLModeChoice() \ No newline at end of file diff --git a/pmml-rexp/src/test/R/data.R b/pmml-rexp/src/test/R/data.R index 449e3a7..eb4e965 100644 --- a/pmml-rexp/src/test/R/data.R +++ b/pmml-rexp/src/test/R/data.R @@ -71,6 +71,20 @@ createIris = function(iris){ storeCsv(irisNA, "IrisNA") } +loadModeChoice = function(){ + data = read.table("http://www.apollochoicemodelling.com/files/examples/data/apollo_modeChoiceData.csv", sep = ",", header = TRUE) + + return (data) +} + +createModeChoice = function(){ + modeChoice = loadModeChoice() + + modeChoice = subset(modeChoice, modeChoice$RP == 1) + + storeCsv(modeChoice, "ModeChoice") +} + loadWineQuality = function(color){ data = read.table(paste("http://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-", color, ".csv", sep = ""), sep = ";", header = TRUE) @@ -109,4 +123,5 @@ data(iris) createAudit(audit) createAuto() createIris(iris) +createModeChoice() createWineQuality() diff --git a/pmml-rexp/src/test/R/util.R b/pmml-rexp/src/test/R/util.R index 727d6d8..de8871e 100644 --- a/pmml-rexp/src/test/R/util.R +++ b/pmml-rexp/src/test/R/util.R @@ -30,6 +30,12 @@ loadIrisCsv = function(name){ return (iris) } +loadModeChoiceCsv = function(name){ + modeChoice = loadCsv(name) + + return (modeChoice) +} + loadVersicolorCsv = function(name){ versicolor = loadCsv(name) versicolor$Species = as.factor(versicolor$Species) diff --git a/pmml-rexp/src/test/java/org/jpmml/rexp/testing/MaxLikConverterTest.java b/pmml-rexp/src/test/java/org/jpmml/rexp/testing/MaxLikConverterTest.java new file mode 100644 index 0000000..58bb4bb --- /dev/null +++ b/pmml-rexp/src/test/java/org/jpmml/rexp/testing/MaxLikConverterTest.java @@ -0,0 +1,29 @@ +/* + * Copyright (c) 2024 Villu Ruusmann + * + * This file is part of JPMML-R + * + * JPMML-R is free software: you can redistribute it and/or modify + * it under the terms of the GNU Affero General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * JPMML-R is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU Affero General Public License for more details. + * + * You should have received a copy of the GNU Affero General Public License + * along with JPMML-R. If not, see . + */ +package org.jpmml.rexp.testing; + +import org.junit.Test; + +public class MaxLikConverterTest extends RExpEncoderBatchTest { + + @Test + public void evaluateIris() throws Exception { + evaluate("MNL", "ModeChoice"); + } +} \ No newline at end of file diff --git a/pmml-rexp/src/test/resources/csv/MNLModeChoice.csv b/pmml-rexp/src/test/resources/csv/MNLModeChoice.csv new file mode 100644 index 0000000..7e5cc04 --- /dev/null +++ b/pmml-rexp/src/test/resources/csv/MNLModeChoice.csv @@ -0,0 +1,1001 @@ +probability(car),probability(bus),probability(air),probability(rail),choice +0.0722337126299313,0.0540537696420912,0.381223368219508,0.49248914950847,rail +0.0454329883100318,0.0339983117972074,0.290648828160121,0.62991987173264,rail +0.54201247373191,0.109798980983945,0.0279282443852395,0.320260300898906,car +0.563619603810126,0.129030795244216,0.0293090087572302,0.278040592188427,car +0.0523397771261674,0.0391667844956363,0.462898506418545,0.445594931959652,air +0.0527923352483652,0.0395054417734682,0.235825854254669,0.671876368723497,rail +0.0538316214541581,0.159489091572616,0.240468394808012,0.546210892165214,rail +0.0602205493727015,0.173923640519051,0.326682858543715,0.439172951564533,rail +0.0396311124237763,0.0788011739065054,0.260600709079781,0.620967004589938,rail +0.0569049978984154,0.13775820669689,0.366881422262451,0.438455373142244,rail +0.0456767228161892,0.149675932571577,0.567233088663837,0.237414255948397,air +0.0490569138447344,0.160115133973363,0.292995334855026,0.497832617326876,rail +0.207410196994729,0.128697144170652,0.260004808262398,0.403887850572221,rail +0.261335145968199,0.0865164634607569,0.23763704502216,0.414511345548884,rail +0.0697367639993746,0.185611576057044,0.0499100437801576,0.694741616163424,rail +0.0483599097751749,0.159293599964766,0.0346108003248486,0.75773568993521,rail +0.240483103159203,0.0890766403312646,0.303818264719643,0.366621991789889,rail 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