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The project will have two basic functions.It will show how accurate the predictive model is using known data.It will give a prediction given a test

The project will have two basic functions.It will show how accurate the predictive model is using known data.It will give a prediction given a test car.To keep everything consistent here are the fewest classes you must develop.PredictorTester, Predictor, Car. Your Predictor class will implement the PredictorADT interface

Your Car class will implement the CarADT interface

PredictorADT.java (constructor: (String filename))

public interface PredictorADT {

public double getTrainingAccuracy ();

publicString getPrediction (CarADT instance);

}

CarADT.java (constructors: () no parameters & (String, String, int, int, String, String, String)

public interface CarADT {

public void setBuying (String s);

public void setMaint (String m);

public void setDoors (int numDoors); // set more as 5

public void setPersons (int numPersons ); // set more as 5

public void setTrunk(String t);

public void setSafety (String s);

public void setRating (String c);

public String getRating();

}

First, develop and test the Car class using code in the PredictorTester. This class will store information about a single car. Second, build and test thePredictorclass. You will need to open,readand storethe carTrain.data file. Then,you will develop the getPrediction(CarADT instance) method. The parameter will be a Car,you can assumewith all attributes set except the Class. The method will return either unacc, acc, good, or vgood based on thecomparison of the input car and the training data. Finally, you will develop the getTrainingAccuracy() method which will call getPrediction for each of the Car(s) in the data set. You will compare the return from getPrediction and the known class for the car and see if they match. Keep track of the number correct and return the ratio of number correct / total number tested.

carTrain.data File info:

vhigh,vhigh,2,2,small,low,unacc vhigh,vhigh,2,2,small,med,unacc vhigh,vhigh,2,2,med,med,unacc vhigh,vhigh,2,2,med,high,unacc vhigh,vhigh,2,2,big,low,unacc vhigh,vhigh,2,2,big,med,unacc vhigh,vhigh,2,2,big,high,unacc vhigh,vhigh,2,4,small,low,unacc vhigh,vhigh,2,4,small,high,unacc vhigh,vhigh,2,4,med,high,unacc vhigh,vhigh,2,4,big,low,unacc vhigh,vhigh,2,4,big,high,unacc vhigh,vhigh,2,more,small,low,unacc vhigh,vhigh,2,more,small,med,unacc vhigh,vhigh,2,more,small,high,unacc vhigh,vhigh,2,more,med,high,unacc vhigh,vhigh,2,more,big,low,unacc vhigh,vhigh,2,more,big,med,unacc vhigh,vhigh,2,more,big,high,unacc vhigh,vhigh,3,2,small,low,unacc vhigh,vhigh,3,2,small,med,unacc vhigh,vhigh,3,2,small,high,unacc vhigh,vhigh,3,2,med,low,unacc vhigh,vhigh,3,2,big,low,unacc vhigh,vhigh,3,2,big,med,unacc vhigh,vhigh,3,2,big,high,unacc vhigh,vhigh,3,4,small,low,unacc vhigh,vhigh,3,4,small,med,unacc vhigh,vhigh,3,4,small,high,unacc vhigh,vhigh,3,4,med,low,unacc vhigh,vhigh,3,4,med,med,unacc 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med,low,4,more,med,med,good med,low,5more,4,small,high,good med,low,5more,4,med,med,good med,low,5more,4,big,med,good med,low,5more,more,small,high,good med,low,5more,more,big,med,good low,med,2,4,small,high,good low,med,2,4,big,med,good low,med,2,more,med,high,good low,med,2,more,big,med,good low,med,3,4,small,high,good low,med,3,4,med,high,good low,med,3,more,small,high,good low,med,3,more,med,med,good low,med,3,more,big,med,good low,med,4,4,small,high,good low,med,4,4,med,med,good low,med,4,4,big,med,good low,med,4,more,med,med,good low,med,4,more,big,med,good low,med,5more,4,small,high,good low,med,5more,4,med,med,good low,med,5more,4,big,med,good low,med,5more,more,small,high,good low,med,5more,more,med,med,good low,med,5more,more,big,med,good low,low,2,4,small,high,good low,low,2,4,med,high,good low,low,2,more,med,high,good low,low,2,more,big,med,good low,low,3,4,small,high,good low,low,3,4,med,high,good low,low,3,more,small,high,good low,low,4,4,med,med,good 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