Example of K Nearest Neighbors with Categorical Response | JMP 13.2

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Predictive and Specialized Modeling • K Nearest Neighbors • Example of K Nearest Neighbors with Categorical Response

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Example of K Nearest Neighbors with Categorical Response

You have historical financial data for 5,960 customers who applied for home equity loans. Each customer was classified as being a Good Risk or Bad Risk. There is missing data on most of the predictors. You want to construct a model to use in classifying the credit risk of future customers.

1.

Select Help > Sample Data and open Equity.jmp.

2.

Select Analyze > Predictive Modeling > K Nearest Neighbors.

3.

Select BAD and click Y, Response.

Because one of the potential predictors, DEBTINC, has many missing values that might be informative, you do not include it in your model.

4.

Select LOAN through CLNO and click X, Factor.

5.

Select Validation and click Validation.

6.

K Nearest Neighbors Report

For each value of K, K Nearest Neighbors constructs a model using only the Training Set observations. Each of these models is used to classify the Validation Set observations. In this example, based on the Validation Set results, a model based on the single nearest neighbor (K = 1) has the smallest misclassification rate. The Test Set verifies that the single nearest neighbor model is the best performer for independent data.

7.

Click the K Nearest Neighbors red triangle and select Publish Prediction Formula.

8.

Next to Number of Neighbors, K, type 1.

This action saves the prediction equation in Formula Depot. Now you can fit other models using other techniques and compare their performance with that of the K = 1 nearest neighbor model using the Model Comparison platform within Formula Depot.

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Help created on 9/19/2017