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diff --git a/src/Chapter4/classification/bayes/TestNBC.java b/src/Chapter4/classification/bayes/TestNBC.java
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+++ b/src/Chapter4/classification/bayes/TestNBC.java
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+package Chapter4.classification.bayes;
+
+import java.io.FileReader;
+import java.io.IOException;
+
+import com.google.gson.JsonObject;
+import com.google.gson.JsonStreamParser;
+
+public class TestNBC {
+	public static void main(String[] args){
+		
+		String filename = args.length >= 1 ? args[0] : "owsemoticons.json";
+		
+		//initialize the sentiment classifier
+		NaiveBayesSentimentClassifier nbsc = new NaiveBayesSentimentClassifier();
+        
+		try {
+			//read the file, and train each document
+			JsonStreamParser parser = new JsonStreamParser(new FileReader(filename));
+			JsonObject elem;
+			String text;
+			while (parser.hasNext()) {
+	            elem = parser.next().getAsJsonObject();
+	            text = elem.get("text").getAsString();
+	            nbsc.trainInstance(text);
+			}
+			
+			//print out the positive and negative dictionary
+			System.out.println("=== Positive Dictionary ===");
+			System.out.println(nbsc.printWordOccurs(0, 25));
+			System.out.println("=== Negative Dictionary ===");
+			System.out.println(nbsc.printWordOccurs(1, 25));
+			
+	        //now go through and classify each line as positive or negative
+//			parser = new JsonStreamParser(new FileReader(filename));
+//			while (parser.hasNext()) {
+//	            elem = parser.next().getAsJsonObject();
+//	            text = elem.get("text").getAsString();
+//	            Classification c = nbsc.classify(text);
+//	            System.out.println(c + " -> " + text);
+//			}
+			System.out.println(nbsc.classify("I love new york"));
+			
+		} catch (IOException e) {
+			e.printStackTrace();
+		}
+		
+	}
+}