Greedy optimization algorithm. by Alexis Bénichou (19832361)

“…The horizontal orange dashed line indicates the codelength of the corresponding simple graph model without motifs (see Motif-free reference codes). (D) The algorithm is run a hundred times for each dyadic base model and the most compressing model is selected. …”

Available habitat across a portion of the study landscape projected for each species type based on selected solutions. by Max D. Jones (6269006)

Layout of the EEG channel selections in the measurement. by Dovilė Kurmanavičiūtė (21072549)

Dice and 95HD results of the different selection strategies. by Guoping Shan (8999381)

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

“…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. …”

Selection and quantification of text indicators. by Zhiheng Zhang (9347282)

Character selection and extraction comparison. by Zhiheng Zhang (9347282)

Three machine learning algorithms were further employed to select candidate key hub genes. by Zhifeng Wu (303016)

“…(C, D) The Support Vector Machine Recursive Feature Elimination (SVM-RFE) algorithm was used to select significant feature genes from the 20 candidate genes. …”

Screening criteria applied for the study selection process. by Yong Lin Lai (20854961)

Path data for different algorithms in four different environments. by Tengfei Ma (597633)

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Throughput versus SNR for proposed and conventional power allocation algorithms. by Emad S. Hassan (17775798)

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Overview of the proposed methodology for the ML regressor selection process and model evaluation. by Marwah Salman (22593380)

Selection of advanced nodes. by Fazia Akhtar (21453122)

The selected parameters and the corresponding sub-parameter values. by Muhammad Abdullah (3357692)

Flowchart of the 3D-NLE-BF algorithm. by Haiyan Zhang (176919)

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Improved random forest algorithm. by Zhen Zhao (159931)

“…The results showed that utilizing feature selection methods improves model accuracy to varying degrees compared with RF based on all factors, and the MDA-RF had the lowest MAPE of 0.174 and the highest R² of 0.913 among them. …”

K-means++ clustering algorithm. by Zhen Zhao (159931)

“…The results showed that utilizing feature selection methods improves model accuracy to varying degrees compared with RF based on all factors, and the MDA-RF had the lowest MAPE of 0.174 and the highest R² of 0.913 among them. …”

Voice-based T2D status detection algorithms’ overall performance. by Abir Elbéji (13988706)

Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

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