public void KNNClassifierMain(String[] args) throws IOException {
		// TODO Auto-generated method stub
		//wordMapԴʵĴʵ<ʣĵгֵĴ>
		double[] accuracyOfEveryExp = new double[10];
		double accuracyAvg,sum = 0;
		KNNClassifier knnClassifier = new KNNClassifier();
		NaiveBayesianClassifier nbClassifier = new NaiveBayesianClassifier();
		Map<String,Double> wordMap = new TreeMap<String,Double>();
		Map<String,Double> IDFPerWordMap = new TreeMap<String,Double>();	
		ComputeWordsVector computeWV = new ComputeWordsVector();
		wordMap = computeWV.countWords("F:/DataMiningSample/processedSample_includeNotSpecial", wordMap);
		IDFPerWordMap = computeWV.computeIDF("F:/DataMiningSample/processedSampleOnlySpecial",wordMap);
		computeWV.printWordMap(wordMap);
		//KNN㷨10ҪĵTFļ
		for(int i = 0; i < 10; i++){
			computeWV.computeTFMultiIDF("F:/DataMiningSample/processedSampleOnlySpecial",0.9, i, IDFPerWordMap,wordMap);
			String trainFiles = "F:/DataMiningSample/docVector/wordTFIDFMapTrainSample"+i;
			String testFiles = "F:/DataMiningSample/docVector/wordTFIDFMapTestSample"+i;
			String kNNResultFile = "F:/DataMiningSample/docVector/KNNClassifyResult"+i;
			String kNNRightFile = "F:/DataMiningSample/docVector/KNNClassifyRight"+i;
			accuracyOfEveryExp[i] = knnClassifier.doProcess(trainFiles, testFiles, kNNResultFile);
			knnClassifier.createRightFile(kNNResultFile,kNNRightFile);
			accuracyOfEveryExp[i] = nbClassifier.computeAccuracy(kNNResultFile, kNNRightFile);//׼ȷʸñҶ˹㷨еķ
			sum += accuracyOfEveryExp[i];
			System.out.println("The accuracy for KNN Classifier in "+i+"th Exp is :" + accuracyOfEveryExp[i]);
		}
		accuracyAvg = sum / 10;
		System.out.println("The average accuracy for KNN Classifier in all Exps is :" + accuracyAvg);
	}