Perceptron.java: Implement the Perceptron constructor, Perceptron(int n), and the method, int numberOfInputs(). a. Test: In the main() method, instantiate a few Perceptron objects and print the number of inputs for each object. 2. Implement the String toString() method. a. Test: In the main() method, print the various Perceptron objects. What should the output be for a newly instantiated Perceptron object? 3. Implement the double weightedSum(double[] x) method. a. Test: In the main() method, print the result of invoking the weightedSum method on the various Perceptron objects (using, of course, appropriately sized arrays. 4. Implement the int predict(double[] x) method. 5. Implement the void train(double[] x, int label) method. Note - train should call predict.

Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Perceptron.java:

  1. Implement the Perceptron constructor, Perceptron(int n), and the method, int numberOfInputs().

a. Test: In the main() method, instantiate a few Perceptron objects and print the number of inputs for each object.  

2. Implement the String toString() method. 

a. Test: In the main() method, print the various Perceptron objects.  What should the output be for a newly instantiated Perceptron object?

3. Implement the double weightedSum(double[] x) method. 

a. Test: In the main() method, print the result of invoking the weightedSum method on the various Perceptron objects (using, of course, appropriately sized arrays.

4. Implement the int predict(double[] x) method.  

5. Implement the void train(double[] x, int label) method.  Note - train should call predict. 

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