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CO Task 5

In this homework, we explore Naïve Bayes, K-Nearest Neighbors, and Support Vector Machine models.

1) (50 points) Use “credit_Dataset.arff” dataset and apply the Naïve Bayes, K-Nearest Neighbors, and Support Vector Machine technique using the WEKA tool in 2 different settings, including:

a. 10 fold-cross validation.

b. 80% training.

Write a short paragraph about your findings and compare the results (accuracy). Use a table or a bar chart graph (MS Excel) to visualize the results.

2) (25 points) Use “credit_Dataset.arff” dataset and apply the K-Nearest Neighbors with different K values (1, 3, 5, 15). Visualize the results corresponding to different K values using a bar chart graph.

3) (25 points) Use “credit_Dataset.arff” dataset and apply the Support Vector Machine using three different Kernels. Write a short paragraph about your findings and compare the results.

Deliverable:

• Your report including the screenshots of your implementation and the result.

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