Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary test » binary depot (Expand Search)
data model » data models (Expand Search)
test based » test cases (Expand Search), test case (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary test » binary depot (Expand Search)
data model » data models (Expand Search)
test based » test cases (Expand Search), test case (Expand Search)
-
1
<i>hi</i>PRS algorithm process flow.
Published 2023“…<p><b>(A)</b> Input data is a list of genotype-level SNPs. <b>(B)</b> Focusing on the positive class only, the algorithm exploits FIM (<i>apriori</i> algorithm) to build a list of candidate interactions of any desired order, retaining those that have an empirical frequency above a given threshold <i>δ</i>. …”
-
2
-
3
-
4
-
5
-
6
-
7
-
8
-
9
-
10
-
11
Friedman average rank sum test results.
Published 2025“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
-
12
-
13
-
14
Flowchart scheme of the ML-based model.
Published 2024“…<b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …”
-
15
-
16
-
17
-
18
-
19
Analysis and design of algorithms for the manufacturing process of integrated circuits
Published 2023“…From this, we propose: (i) a new ILP model, and (ii) a new solution representation, which, unlike the reference work, guarantees that feasible solutions are obtained throughout the generation of new individuals. Based on this new representation, we proposed and evaluated other approximate methods, including a greedy algorithm and a genetic algorithm that improve the state-of-the-art results for test cases usually used in the literature. …”
-
20