Search alternatives:
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary test » binary depot (Expand Search)
test based » test cases (Expand Search), test case (Expand Search)
b feature » _ feature (Expand Search), a feature (Expand Search), _ features (Expand Search)
binary b » binary _ (Expand Search)
feature optimization » resource optimization (Expand Search), feature elimination (Expand Search), structure optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary test » binary depot (Expand Search)
test based » test cases (Expand Search), test case (Expand Search)
b feature » _ feature (Expand Search), a feature (Expand Search), _ features (Expand Search)
binary b » binary _ (Expand Search)
-
1
-
2
-
3
-
4
-
5
-
6
-
7
-
8
-
9
-
10
Design and implementation of the Multiple Criteria Decision Making (MCDM) algorithm for predicting the severity of COVID-19.
Published 2021“…P <0.05 was considered statistically significant. (B). The MCDM algorithm-Stage 2. Feature Ranking, this stage is the process of using the TOPSIS method to rank features. …”
-
11
-
12
-
13
-
14
<i>hi</i>PRS algorithm process flow.
Published 2023“…The sequences can include from a single SNP-allele pair up to a maximum number of pairs defined by the user (<i>l</i><sub>max</sub>). <b>(C)</b> The whole training data is then scanned, searching for these sequences and deriving a re-encoded dataset where interaction terms are binary features (i.e., 1 if sequence <i>i</i> is observed in <i>j</i>-th patient genotype, 0 otherwise). …”
-
15
-
16
-
17
-
18
Flowchart scheme of the ML-based model.
Published 2024“…<b>F)</b> Feature extraction using three different steps: <b>Fi)</b> Color moments in different orders based on color distribution. …”
-
19
-
20
Feature selection results.
Published 2025“…Further integrate the binary variant of OcOA (bOcOA) for effective feature selection, which reduces the average classification error to 0.4237 and increases CNN accuracy to 93.48%. …”