Code and data. by Crispin H. V. Cooper (21484906)

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Code. by Wenyuan Xu (2553028)

Data&Code by anonymous author (20478659)

Data&Codes.rar by anonymous author (20478659)

Line charts of the elbow method and the k-value selection algorithm: (A) elbow method; (B) k-value selection algorithm. by Jingnan Yan (20727331)

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Code might be found under: https://kaggle.com/code/agatasko/anomalies-graph-networks. by Agata Skorupka (20469080)

Visualization of algorithm detection results. by Xinpeng Yao (18882573)

“…<div><p>Aiming at the problem that small and irregular detection targets such as cyclists have low detection accuracy and inaccurate recognition by existing 3D target detection algorithms, MAT-PointPillars (Multi-scale Attention and Transformer PointPillars), a 3D object detection algorithm, extends PointPillars with multi-scale vision Transformers and attention mechanisms. …”

Local Means Thresholding Algorithm shows high robustness. by Araven Tiroumalechetty (17827252)

S1 Data - CSW-YOLO: A traffic sign small target detection algorithm based on YOLOv8 by Qian Shen (89639)

Subjects: “…existing mainstream algorithms…”

Variable selection for microbiome data. by Evan Gorstein (20553314)

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Variable selection for GWAS data. by Evan Gorstein (20553314)

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Hyperspectral Camouflage Detection Dataset and Codes by Qiran Wang (22051883)

Proposed genetic algorithm for feature selection. by Shirin Dehghan (19837936)

“…Using GA, Random Forest also demonstrated strong performance, achieving an accuracy rate of 87.4%. Genetic Algorithm significantly improved the performance of all classifiers, emphasizing the importance of feature selection. …”

Variable selection for gene expression data. by Evan Gorstein (20553314)

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Runtime of fitting algorithm (for single λ) on each of three real omics data sets. by Evan Gorstein (20553314)

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Predicted sensitivity, specificity, PPV, and NPV of the four algorithms (a, b) and algorithms combinations (c, d) under Model-3 in the primary analysis. by Jia Wei (120974)

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Algorithms included in Neuroptimus. by Máté Mohácsi (20469514)

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

“…In addition, used in conjunction with the KNN classifier, IRBMO significantly improves the classification accuracy, with an average accuracy improvement of 43.89% on 12 medical datasets compared to the original Red-billed Blue Magpie algorithm. These results demonstrate the potential and wide applicability of IRBMO in feature selection for medical data.…”

The folder containing the code is provided as supportive documentation associated with this paper. by Quxi Kuang (22493270)

A sample demonstration of DBCAA algorithm for 4 observers. by Abdulkerim Capar (20390120)