بدائل البحث:
based optimization » whale optimization (توسيع البحث)
iii optimization » _ optimization (توسيع البحث), fox optimization (توسيع البحث), art optimization (توسيع البحث)
binary models » primary models (توسيع البحث), final models (توسيع البحث)
models based » model based (توسيع البحث)
class iii » class ii (توسيع البحث), class i (توسيع البحث)
based optimization » whale optimization (توسيع البحث)
iii optimization » _ optimization (توسيع البحث), fox optimization (توسيع البحث), art optimization (توسيع البحث)
binary models » primary models (توسيع البحث), final models (توسيع البحث)
models based » model based (توسيع البحث)
class iii » class ii (توسيع البحث), class i (توسيع البحث)
-
1
-
2
Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
منشور في 2022"…However, ToxCast assays differ in the amount of data and degree of class imbalance (CI). Therefore, the resampling algorithm employed should vary depending on the data distribution to achieve optimal classification performance. …"
-
3
ROC curve for binary classification.
منشور في 2024"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. …"
-
4
Confusion matrix for binary classification.
منشور في 2024"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. …"
-
5
<i>hi</i>PRS algorithm process flow.
منشور في 2023"…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …"
-
6
-
7
-
8
MSE for ILSTM algorithm in binary classification.
منشور في 2023"…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"
-
9
Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
منشور في 2025الموضوعات: -
10
Summary of existing CNN models.
منشور في 2024"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. …"
-
11
DE algorithm flow.
منشور في 2025"…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
-
12
Test results of different algorithms.
منشور في 2025"…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …"
-
13
-
14
Testing results for classifying AD, MCI and NC.
منشور في 2024"…The proposed model yielded notable results, such as an accuracy of 93.45% and an area under the curve value of 0.99 when trained on the three classes. …"
-
15
Algorithm for generating hyperparameter.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
-
16
Results of machine learning algorithm.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
-
17
-
18
ROC comparison of machine learning algorithm.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
-
19
Ensemble model architecture.
منشور في 2024"…To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …"
-
20
QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
منشور في 2020"…The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"