Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Comparison results of prediction model with single algorithm and combination algorithm. by Jiayuan Wang (3765376)

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Evaluation of model aggregation algorithms. by JiaMing Wang (334865)

“…Additionally, the paper introduces the Gradient Similarity Model Aggregation (GSA) algorithm, which dynamically selects and weights updates from different models to reduce communication overhead. …”

Schematic representation of genetic algorithm (GA) as an evolutionary optimization algorithm. by Mohammad Reza Najafi (9288989)

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Evaluation metrics of the models constructed by each algorithm. by Xiaoyan Yang (259084)

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ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Comparison of homomorphic encryption algorithms. by JiaMing Wang (334865)

“…Additionally, the paper introduces the Gradient Similarity Model Aggregation (GSA) algorithm, which dynamically selects and weights updates from different models to reduce communication overhead. …”

Flow diagram of FPA-WPA algorithm. by Jiayuan Wang (3765376)

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Comparison of different optimization algorithms. by Hang Zhao (143592)

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Performance of models by different algorithms. by Yong Zhang (5893)

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Development of the CO₂ Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms by Hossein Mashhadimoslem (11456548)

Algorithm deployment platform build. by Jie Wang (16762)

Algorithm steps for house price prediction model. by Xuan Wang (55634)

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Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

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Convergence curves of various algorithms under test functions. by Jiayuan Wang (3765376)

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Bagging Model Algorithm Flow. by Wen Yu (384130)

The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Parameters of the machine learning algorithms used in the study. by Xiaoyan Yang (259084)

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Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip by Cong Peng (160287)

“…</p>Materials and methods<p>This study retrospectively analyzed data from 1,620 patients with extremely aggressive prostate cancer in the SEER database (2000–2020). …”

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip by Cong Peng (160287)

“…</p>Materials and methods<p>This study retrospectively analyzed data from 1,620 patients with extremely aggressive prostate cancer in the SEER database (2000–2020). …”