Figure 6 - uploaded by Sandra Benítez-Peña
Content may be subject to copyright.
Download
View publication
MSE for the positive class probability predictions of each dataset. Method for Controlling 1

MSE for the positive class probability predictions of each dataset. Method for Controlling 1

Source publication
Figure 2: Histogram of scores for a single instance when a k-fold CV is...
Figure 3: Histogram of scores for a single instance when the Bootstrap...
Figure 4: Flowchart of the Bootstrap-based methodology
Figure 5: Control over the probabilities estimation. In Subfigures 5(a)...
+3 Figure 6: MSE for the positive class probability predictions of each...
Cost-sensitive probabilistic predictions for support vector machines
Preprint
Full-text available
  • May 2020
Support vector machines (SVMs) are widely used and constitute one of the best examined and used machine learning models for 2-class classification. Classification in SVM is based on a score procedure, yielding a deterministic classification rule, which can be transformed into a probabilistic rule (as implemented in off-the-shelf SVM libraries), but...
Cite
Download full-text

Contexts in source publication

Context 1
... all the figures, the class of interest to be controlled is assumed to be the positive one. Figures 6 and 7 show the MSE when considering only the positive instances, while Figures 8 and 9 depict the MSE for the negative instances. ...
Context 2
... Figures 6 and 7, we can see how as the threshold for obtaining a given proportion of the instances in the correct class (x-axis) is moved to the right, the MSE becomes lower, as expected. In fact, there are some datasets (banknote, divorce, leukemia, SRBCT and wisconsin), for which the obtained MSEs are very close to 0, for both Figures 6 and 7. ...