0.00 0.05 0.10 0.15 0.20 Error Rate Training Errors Test Errors 0.01 0.02 0.05 0.10 0.20 0.50 1.00 1/K FIGURE 2.17. The KNN training error rate (blue, 200 observations) and test error rate (orange, 5,000 observations) on the data from Figure 2.13, as the level of flexibility (assessed using 1/K on the log scale) increases, or equivalently as the number of neighbors K decreases. The black dashed line indicates the Bayes error rate. The jumpiness of the curves is due to the small size of the training data set.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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What would be the best range of k values that produce the best test error for this KNN model?

0.00
0.05
0.10
0.15
0.20
Error Rate
Training Errors
Test Errors
0.01
0.02
0.05
0.10
0.20
0.50
1.00
1/K
FIGURE 2.17. The KNN training error rate (blue, 200 observations) and test
error rate (orange, 5,000 observations) on the data from Figure 2.13, as the level
of flexibility (assessed using 1/K on the log scale) increases, or equivalently as
the number of neighbors K decreases. The black dashed line indicates the Bayes
error rate. The jumpiness of the curves is due to the small size of the training
data set.
Transcribed Image Text:0.00 0.05 0.10 0.15 0.20 Error Rate Training Errors Test Errors 0.01 0.02 0.05 0.10 0.20 0.50 1.00 1/K FIGURE 2.17. The KNN training error rate (blue, 200 observations) and test error rate (orange, 5,000 observations) on the data from Figure 2.13, as the level of flexibility (assessed using 1/K on the log scale) increases, or equivalently as the number of neighbors K decreases. The black dashed line indicates the Bayes error rate. The jumpiness of the curves is due to the small size of the training data set.
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