Algorithm process of BPNN. by Xiaoxiang Cao (12644851)

The details of the test algorithm. by Yule Sun (16015342)

“…To investigate the optimization ability of the DMBBPSO for single-objective optimization problems, The CEC2017 benchmark functions are used in experiments. Five state-of-the-art evolutionary algorithms are used in the control group. …”

GraSPy: an Open Source Python Package for Statistical Connectomics by Benjamin Pedigo (6580352)

“…We developed GraSPy, an open-source Python toolkit for statistical inference on graphs. …”

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

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List of Abbreviations by Gursimran Singh (575288)

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The results of ICA performed using PyNoetic. by Gursimran Singh (575288)

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Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

The workflow used to analyze imbalanced and balanced sequences. by Solomon Shiferaw Beyene (9143178)

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)

DataSheet2_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV by Jian-Kun Song (11711756)

“…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”

DataSheet3_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.CSV by Jian-Kun Song (11711756)

“…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”

DataSheet1_Classification and biomarker gene selection of pyroptosis-related gene expression in psoriasis using a random forest algorithm.pdf by Jian-Kun Song (11711756)

“…Subsequently, a novel diagnostic model comprising PRGs for psoriasis was constructed using a random forest algorithm (ntree = 400). A receiver operating characteristic (ROC) analysis was used to evaluate the classification performance through both internal and external validation. …”

F1-scores of anomaly detection algorithms. by GaoXiang Zhao (21499525)

“…Empirical evaluations conducted on multiple benchmark datasets demonstrate that the proposed method outperforms classical anomaly detection algorithms while surpassing conventional model averaging techniques based on minimizing standard loss functions. …”

Table1_nPCA: a linear dimensionality reduction method using a multilayer perceptron.DOCX by Juzeng Li (17748507)

Simulation settings of rMAPPO algorithm. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Parameters of the proposed algorithm. by Heba Askr (15572851)

“…First, MaAVOA was applied to the DTLZ functions, and its performance was compared to that of several popular many-objective algorithms and according to the results, MaAVOA outperforms the competitor algorithms in terms of inverted generational distance and hypervolume performance measures and has a beneficial adaptation ability in terms of both convergence and diversity performance measures. …”

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Overlays of the gates drawn for the same 12 samples sorted both by hand and with the automation show similar gated populations. by Diane M. Wiener (1956583)

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.…”