The Bridge - Issue 2, 2018 - 15

Determining Optimum Drop-out Rate for Neural Networks

were run across the dropout rates, and the averaged
resulting model accuracies are shown in
FIgure 5 (b).

Furthermore, the occurrence of default is relatively
uncommon. Therefore, the randomly picked 230
sample testing set can range significantly in its
proportion of defaulting clients.

(a)

Figure 6: Different trials for the averaged data seen in
Figure 5(b).

(b)

Figure 5: Impact of dropout rate on a credit card training
set of 450 samples while using large and small testing
sets (a) The credit card dataset containing 1000 samples
in the testing set (b) The credit card dataset containing
230 samples in the testing set

Much of the variation shown in Figure 5(b) is not
repeatable from one set of trials to another. Figure
5(b) averages the results of five different trials.
Figure 6 shows the first four trials that were used to
construct the averaged curve in Figure 5(b). Figure
6 shows that the model accuracy is inconsistent
between trials. This negates the confidence of
possible conclusions drawn from Figure 5(b). The
credit card default dataset likely has too many
variables and complexity for a 230 sample testing
set to consistently gauge the model accuracies.

Figure 7 shows that the model performance for
the bank dataset is not significantly affected by the
dropout rate. It is difficult to determine an optimum
dropout rate with a high of confidence due to the
small change in performance, which is less than
0.5%. If models trained on such datasets are not
affected by the dropout rate, then no optimum
dropout rate can be determined. Thus, it is not
possible for such datasets to share an optimum
dropout rate.

Figure 7: Performance of model trained on a 28,000
sample bank marketing dataset

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Table of Contents for the Digital Edition of The Bridge - Issue 2, 2018

Contents
The Bridge - Issue 2, 2018 - Cover1
The Bridge - Issue 2, 2018 - Cover2
The Bridge - Issue 2, 2018 - Contents
The Bridge - Issue 2, 2018 - 4
The Bridge - Issue 2, 2018 - 5
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