IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

“…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. …”

IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

“…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. …”

A classification scheme of bipartite randomization algorithms, based on whether the matrix row and columns sums are preserved exactly (Fixed, <i>F</i>), preserved on average (Proportional, <i>P</i>), or unconstrained (Equiprobable, <i>E</i>). by Zachary P. Neal (9946331)

Data Sheet 1_Comparing supervised classification algorithm–feature combinations for Spartina alterniflora extraction: a case study in Zhanjiang, China.pdf by Qiujie Chen (21644732)

“…Here, we combined five supervised classification algorithms—random forest (RF), support vector machine, maximum likelihood classification (MLC), minimum distance classification, and Mahalanobis distance classification—with spectral bands, spectral indices, and the gray-level co-occurrence matrix (GLCM) derived from Sentinel-2 imagery to identify the optimal combination for monitoring the spatial distribution of S. alterniflora on Donghai Island, Zhanjiang. …”

Previously literatures on feature evaluation for relevance based on linear transformation. by Jia Liu (41593)

Comparing AUROC across Graph Neural Networks patient-centric graphs (directed, reversed directed and undirected) for the classification of sepsis on complete blood count data (high... by Daniel Walke (21680915)

Train classification decision table. by Jiren CAO (20442214)

“…The model aimed at maximize the corporate revenue and maximize passenger travel benefit, and was solved by large neighborhood search heuristic algorithm and path size logit assignment based on capacity constraint-passenger flow increment accurate algorithm. …”

Comparison of electronic nose based on bionic chamber. by Yeping Shi (14279118)

Subjects:

PR & ROC curve showing the AUC performance of the proposed DRSA-based model on Unseen Data. by Saim Chishti (22272188)

Subjects:

PR & ROC curve showing the AUC performance of the proposed DRSA-based model on Unseen Data. by Saim Chishti (22272188)

Subjects:

Schematic diagram of <i>K</i>-means algorithm. by Guanqun Wang (705958)

“…This paper proposes a customer segmentation framework within the realm of digital marketing, which integrates a reinforcement learning-based differential evolution algorithm with <i>K</i>-means clustering using dimensionality reduction techniques to address challenges in the customer segmentation process. …”

Decision tree algorithms. by Mahbub E. Sobhani (22278967)

“…We have used Random Forest, Bagging, and Boosting (AdaBoost) algorithms and have compared their performances. We have used decision tree (C4.5) as the base classifier of Random Forest and AdaBoost classifiers and naïve Bayes classifier as the base classifier of the Bagging model. …”

Prediction AUC of Strokeformer and the competitor methods on the ten large-scale binary classification datasets. by Maocheng Cao (22127378)

Subjects:

Prediction AUC of Strokeformer and the competitor methods on the nine small-scale binary classification datasets. by Maocheng Cao (22127378)

Subjects:

Dataset Link - An efficient cyber-attack detection and classification in IoT networks with high-dimensional feature set using Levenberg-Marquardt optimized feedforward neural netwo... by Quxi Kuang (22493270)

Results of the sensor data detection model using the 2-classification CMHS dataset. by Tao Yang (184280)

Results of the sensor data detection model using the 2-classification WADI dataset. by Tao Yang (184280)

3D visualization results of risk-based clustering. by Hyeonbin Ji (20485140)

Subjects:

Comparison of GNNs against benchmarks on complete blood count data for sepsis classification (higher values represent better performance) and their required training time. We evalu... by Daniel Walke (21680915)

Comparing AUROC, exploited biases, use cases and issues of Graph Attention Networks on similarity and patient-centric graphs (directed, reversed directed and undirected) for the cl... by Daniel Walke (21680915)