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We have observed that increasing the level of detail in a data set, which is often an interim goal for us as experimentalists, weakens the performance of the most widely used confidence measure, which had heretofore not been explicitly tested for its performance with CIM results.
A commonly used confidence level is 95%.
The conformal predictors published thus far in chemoinformatics used confidence measures (either (v_{j} left( {{mathbf{x}}_{new} } right)) for RFC or (decvalleft( {{mathbf{x}}_{new} } right)) for SVC) [24, 25, 27, 81].
One essential difference between the present study and that of Dodson and Dobolyi (2015) is that we used confidence scales over a wide range (4-, 5-, 20-, and 100-point scales) rather than carving up a 100-point scale in different ways.
The first and most widely used confidence estimation method is the LOD drop-off, or support interval (SI) method [10].
It used confidence estimation along with a support vector machine (SVM) to predict plant promoters.
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In the dark days of the Cold War, the United States and the Soviet Union used "confidence-building" measures of cooperation on small matters to make it easier to deal with the larger concerns of nuclear survival.
In addition, some statisticians -- like William H. Schmidt of Michigan State University, who is the national research coordinator for the Third International Mathematics and Science Study -- question the validity of using confidence intervals for this purpose.
(f) Improved disparity map using confidence measure.
Then, data pruning using confidence measures takes place.
Section 4 discusses data pruning using confidence measures.
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