Performances of Naïve Bayes (NB), Multilayer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), Support Vector Machine (SVM) and K- Nearest Neighbors (KNN). by Solomon Shiferaw Beyene (9143178)

Accuracy, sensitivity, specificity and F-score. by Solomon Shiferaw Beyene (9143178)

The figures showed a comparison of the balanced and imbalanced sequences and performance of classifiers. by Solomon Shiferaw Beyene (9143178)

Mean and covariance estimation of functional data streams by Mingxue Quan (13282368)

Definition for symbols used in node matching. by Shuwen Wang (457921)

“…The distributed parameter learning and consolidation repeat in an iterative fashion until the algorithm converges or terminates. Many FL methods exist to aggregate weights from distributed sites, but most approaches use a <i>static node alignment</i> approach, where nodes of distributed networks are statically assigned, in advance, to match nodes and aggregate their weights. …”

Node matching result. by Shuwen Wang (457921)

“…The distributed parameter learning and consolidation repeat in an iterative fashion until the algorithm converges or terminates. Many FL methods exist to aggregate weights from distributed sites, but most approaches use a <i>static node alignment</i> approach, where nodes of distributed networks are statically assigned, in advance, to match nodes and aggregate their weights. …”

The algorithm for the same-day surgery protocol. by Magnus Tveit (11442200)

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

“…Algorithms trained without auditory variables as features were statistically worse (p < .001) in both the primary measure of area under the curve (0.82/0.78) and the secondary measure of accuracy (72.3%/74.5%) for the Gaussian and kernel algorithms respectively.…”

(a) The volcano plot of GSE89408, where the red scatter represents the upregulated genes and the blue scatter represents the downregulated genes. (b) The heatmap of GSE89408. by Devi Soorya Narayana Sasikumar (22331743)

Experiment 2D and 5D: Progressive Sample Scaling Algorithm To Solve Many-Affine BBOB Functions. by Boris Almonacid (4110337)

“…</p><p dir="ltr">[2] GECCO 2024 Competition: Anytime Algorithms for Many-affine BBOB Functions <a href="https://markdownlivepreview.com/#cite_ref-2" target="_blank">https://gecco-2024.sigevo.org/Competitions#id_Anytime Algorithms for Many-affine BBOB Functions</a>.…”

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

Similarity between the hierarchical community structure of structural and functional brain graphs. by Arian Ashourvan (6685232)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

Payoff spaces under <i>D</i>_<i>i</i> combinations where behavioral switching occurred and under all other <i>D</i>_<i>i</i> combinations of non-behavioral swit... by Hiroyuki Ichijo (13891153)

Fitness curves of the 6 test functions. by Peiwen Zhang (1863202)

Multi-scale detection of hierarchical community architecture in structural and functional brain networks by Arian Ashourvan (6685232)

“…Finally, we build an explicitly multimodal multiplex graph that combines both structural and functional connectivity in a single model, and we identify the topological scales where resting state functional connectivity and underlying structural connectivity show similar <i>versus</i> unique hierarchical community architecture. …”

Computing the objective function. by Xiaochen He (455300)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

Main parameters of braking system. by Honglei Pang (22693724)

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