back-classify and cross-validation demo

back_classify.js

@@ -0,0 +1,24 @@
+console.log("limdu back classification demo start");
+
+var limdu = require('limdu');
+
+// Initialize a multi-label classifier with a feature extractor and past-training-samples:
+var intentClassifier = new limdu.classifiers.EnhancedClassifier({
+	classifierType: limdu.classifiers.multilabel.BinaryRelevance.bind(0, {
+		binaryClassifierType: limdu.classifiers.Winnow.bind(0, {retrain_count: 10})
+	}),
+	featureExtractor: limdu.features.NGramsOfWords(1),
+	pastTrainingSamples: [],
+});
+
+// Train and test:
+intentClassifier.trainBatch([
+	{input: "I want an apple", output: "apl"},
+	{input: "I want a banana", output: "bnn"},
+	{input: "I really want an apple", output: "apl"},
+	{input: "I want a banana very much", output: "bnn"},
+	]);
+
+console.dir(intentClassifier.backClassify("apl"));  // [ 'I want an apple', 'I really want an apple' ]
+
+console.log("limdu back classification demo end");

cross_validation.js

@@ -0,0 +1,47 @@
+console.log("limdu cross-validation demo start");
+
+var limdu = require("limdu");
+
+// define a toy dataset:
+var dataset = [
+           	{input: "I want an apple", output: "apl"},
+        	{input: "I want a banana", output: "bnn"},
+        	{input: "I want chips", output: "cps"},
+           	{input: "I want an apple and a banana", output: ["apl","bnn"]},
+        	{input: "I want a banana and chips", output: ["bnn","cps"]},
+        	{input: "I want chips and an apple", output: ["cps","apl"]},
+           	{input: "I want nothing", output: []},
+        	{input: "I want a banana and chips and an apple", output: ["apl","bnn","cps"]},
+        	{input: "I want chips and a banana and and an apple", output: ["apl","bnn","cps"]},
+        	{input: "I want an apple and chips and a banana", output: ["apl","bnn","cps"]},
+        	];
+var numOfFolds = 5; // for k-fold cross-validation
+
+// Define the type of classifier that we want to test:
+var IntentClassifier = limdu.classifiers.EnhancedClassifier.bind(0, {
+	classifierType: limdu.classifiers.multilabel.BinaryRelevance.bind(0, {
+		binaryClassifierType: limdu.classifiers.Winnow.bind(0, {retrain_count: 10})
+	}),
+	featureExtractor: limdu.features.NGramsOfWords(1),
+});
+
+var microAverage = new limdu.utils.PrecisionRecall();
+var macroAverage = new limdu.utils.PrecisionRecall();
+
+var verbosity = 0;
+
+limdu.utils.partitions.partitions(dataset, numOfFolds, function(trainSet, testSet) {
+	console.log("Training on "+trainSet.length+" samples, testing on "+testSet.length+" samples");
+	var classifier = new IntentClassifier();
+	classifier.trainBatch(trainSet);
+	limdu.utils.test(classifier, testSet, verbosity,
+		microAverage, macroAverage);
+});
+
+macroAverage.calculateMacroAverageStats(numOfFolds);
+console.log("\n\nMACRO AVERAGE:"); console.dir(macroAverage.fullStats());
+
+microAverage.calculateStats();
+console.log("\n\nMICRO AVERAGE:"); console.dir(microAverage.fullStats());
+
+console.log("limdu cross-validation demo end");

lookup_table.js

@@ -12,7 +12,7 @@ var TextClassifier = limdu.classifiers.multilabel.BinaryRelevance.bind(0, {
 // Initialize a classifier with a feature extractor and a lookup table:
 var intentClassifier = new limdu.classifiers.EnhancedClassifier({
 	classifierType: TextClassifier,
-	featureExtractor: limdu.features.NGramsFromText(1),  // each word ("1-gram") is a feature  
+	featureExtractor: limdu.features.NGramsOfWords(1),  // each word ("1-gram") is a feature  
 	featureLookupTable: new limdu.features.FeatureLookupTable()
 });