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

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Filtered Labels after applying the data preparation algorithms. by Tanjim Taharat Aurpa (11250554)

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

“…We find evidence that the generalised GLS-KGR algorithm is well-suited to such time-series applications, outperforming several standard techniques on this dataset.…”

Overview of proposed methodology from data collection to analysis. This methodology finds the change in the teacher-student relationship due to the COVID-19 pandemic. by Md Juwel Ahmed Sarker (20927530)

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The method for determining the chemical constituents of unknown materials in the algorithm. by Dong Hyeok Choi (12562048)

The comparison of results from the proposed architecture and state-of-the-art algorithms on the UNSW-B15, NSL-KDD and KDDCUP’99 dataset. by Abdullah Asım Yılmaz (20715311)

Explained variance of features subsets using different machine learning algorithms: Fig 3 shows all the possible combinations of feature subsets, according to S3 Table in S1 Data, with corresponding explained variance estimated using different machine learning algorithms (Lasso, Ridge Regression, Support Vector Regression (SVR) and Extra Trees). by Qasim Bukhari (20896572)

Model comparison between our model-free algorithm (here MF*) and SARSA. by Carlos A. Velázquez-Vargas (19751567)

“…We found similar results for the data on Experiment 2, with no significant difference in performance between the models for the Single (V = 46, p = 0.13) or the Multiple group (V = 67, p = 0.97) according to AIC, but our model outperformed SARSA for both the Single (V = 31, p = 0.02) and the Multiple group (V = 26, p = 0.01) according to BIC.…”

A* Path-Finding Algorithm to Determine Cell Connections by Max Weng (22327159)

Overview of CINner’s mathematical model and simulation algorithm. by Khanh N. Dinh (20549532)

“…Right: data available to be computed in each step (see S1 Notes). …”

Characteristics of the cohort as extracted from the national registers, stratified according to poststroke epilepsy (PSE) status as verified through medical records. <i><i>P</i></i... by André Idegård (22041446)

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Model’s measure methods. by Songsong Wang (8088293)

Subjects: “…necessitating extensive data…”

Data underlying the findings. by Carol Kotliar (22351525)

A world map classifying countries according to pandemic strategy. by Karl Gauffin (3175503)

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Scatter diagram of different principal elements. by Jizhong Wang (7441697)

Variation of the system output according to the optimized parameters for case 3. by Mohammed Alqahtani (2049139)

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BIC-SAC findings. by Nayeem Ahmad Khan (11727377)

The distribution of SO2 Mean according to different dates after MSD stages: (a) SO2 mean values in the original data. (b) SO2 mean values after the first stage. (c) SO2 mean values... by Tamer Abdel Latif Ali (21464041)

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Data Sheet 1_A method for finding epistatic effects of maternal and fetal variants.docx by Michael Nodzenski (3714730)

“…Though the epistasis-mining algorithms MDR-PDT, TrioFS, and EPISFA-LD were originally designed to find epistatic offspring variants, we generalize them to include maternal SNPs and search more broadly. …”