Information Technology Reference
In-Depth Information
Fig. 10 Predicted-by-
observed chart
For categorical dependent variables, the predicted-by-observed chart displays
clustered boxplots of predicted pseudo-probabilities for the combined training and
testing samples. The x axis corresponds to the observed response categories, and the
legend corresponds to predicted categories.
The leftmost boxplot shows, for cases that have observed category anomaly, the
predicted pseudo-probability of category anomaly. The portion of the boxplot above
the 0.5 mark on the y axis represents correct predictions shown in the confusion
matrix table. The portion below the 0.5 mark represents incorrect predictions. As
shown in the confusion matrix table that the network is excellent at predicting cases
with the anomaly category using the 0.5 cutoff, so only a portion of the lower
whisker and some outlying cases are misclassi
ed. The next boxplot to the right
shows, for cases that have observed category anomaly, the predicted pseudo-
probability of category normal. Since there are only two categories in the target
variable, the
first two boxplots are symmetrical about the horizontal line at 0.5.
The third boxplot shows, for cases that have observed category normal, the
predicted pseudo-probability of category anomaly. It and the last boxplot are
symmetrical about the horizontal line at 0.5. The last boxplot shows, for cases that
have observed category normal, the predicted pseudo-probability of category nor-
mal. The portion of the boxplot above the 0.5 mark on the y axis represents correct
predictions shown in the confusion matrix table. The portion below the 0.5 mark
represents incorrect predictions. Remember from the confusion matrix table that the
network predicts slightly more than half of the cases with the normal category using
the 0.5 cutoff, so a good portion of the box is misclassi
ed. Looking at the plot, it
appears that by lowering the cutoff for classifying a case as normal from 0.5 to
approximately 0.3
—
this is roughly the value where the top of the second box and
Search WWH ::
Custom Search