F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

F1 score of a given number of selected edges on the chain graph dataset. by Tomokaze Shiratori (9635271)

F1 score of a given number of selected edges on the random graph dataset. by Tomokaze Shiratori (9635271)

F1 score of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

The F1 scores for different number of heads for multi-attention. by Peihan Wen (6324315)

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

“…<p>Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.…”

The SSA based SVM objective function minimization against iterations. by Ali Ahmed (2567584)

Subjects:

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Parameters of the genetic algorithm. by Jian Ma (170138)

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

Subjects:

Python cv coding screenshots of all developed fingerprints on distinct surfaces. by Nisha Yadav (366131)

A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

Subjects:

The average convergence curve of the algorithm under different calculation examples ((1)-(28) correspond to functions <i>f1</i>-<i>f28</i> respectively). by Qianhang Du (13410314)

“…<p>The average convergence curve of the algorithm under different calculation examples ((1)-(28) correspond to functions <i>f1</i>-<i>f28</i> respectively).…”

Flowchart of the clinical decision support system and the interpretable tropical geometry-based fuzzy neural network algorithm. by Yufeng Zhang (195768)

Comparison of performance obtained by our approach with other state-of-the-art algorithms. by Sajad Mousavi (6672425)

The structure of genetic algorithm (GA). by Ali Akbar Moosavi (17769033)

“…First, physico-chemical inputs as bulk density (BD), initial water content (W_i), saturated water content (W_s), mean weight diameter (MWD), and geometric mean diameter (GMD) of aggregates, pH, electrical conductivity (EC), and calcium carbonate equivalent (CCE) were measured. Then, radial basis functions (RBFNNs), multilayer perceptron (MLPNNs), hybrid genetic algorithm (GA-NNs), and particle swarm optimization (PSO-NNs) neural networks were utilized to develop PTFs and compared their accuracy with the traditional regression model (MLR) using statistical indices. …”

Differences between average F1 obtained for PFP-WGAN and DeepGO-Seq for the GO terms in each height ( and ). by Seyyede Fatemeh Seyyedsalehi (10196767)

The schematic view of the fruit fly optimization algorithm (FOA). by Mohsen Hesami (6917390)

Subjects:

Performance of LSWOA in qualitative analysis experiment (F1-F8). by Junhao Wei (6816803)

Immune infiltration analysis by ssGSEA algorithm. by Yubin Xue (1537042)