Search alternatives:
robust classification » forest classification (Expand Search), risk classification (Expand Search), group classification (Expand Search)
design optimization » bayesian optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary b » binary _ (Expand Search)
b design » _ design (Expand Search), a design (Expand Search), i design (Expand Search)
robust classification » forest classification (Expand Search), risk classification (Expand Search), group classification (Expand Search)
design optimization » bayesian optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary b » binary _ (Expand Search)
b design » _ design (Expand Search), a design (Expand Search), i design (Expand Search)
-
1
-
2
-
3
Individual Transition Label Noise Logistic Regression in Binary Classification for Incorrectly Labeled Data
Published 2021“…<p>We consider a binary classification problem in the case where some observations in the training data are incorrectly labeled. …”
-
4
-
5
-
6
-
7
-
8
-
9
-
10
-
11
-
12
-
13
-
14
-
15
-
16
-
17
-
18
The Pseudo-Code of the IRBMO Algorithm.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
-
19
IRBMO vs. meta-heuristic algorithms boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”
-
20
IRBMO vs. feature selection algorithm boxplot.
Published 2025“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”