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

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

“…In order to comprehensively verify the performance of IRBMO, this paper designs a series of experiments to compare it with nine mainstream binary optimization algorithms. The experiments are based on 12 medical datasets, and the results show that IRBMO achieves optimal overall performance in key metrics such as fitness value, classification accuracy and specificity. …”

code&data by Liyuan Liu (18298084)

“…The study identified outdoor sports facilities in Shanghai using advanced deep-learning techniques on remote sensing data. It then developed a greedy heuristic algorithm based on the Gaussian Two-Step Floating Catchment Area method and Gini coefficient analysis for evaluating and optimizing facility accessibility and fairness. …”

Prediction of pharmaceuticals occurrence based on sales data and Machine learning algorithms. by Júlia Bijos (14489543)

“…</p><p dir="ltr"><b>Antibioticos/Carbamazepina</b>: contains the main codes of the prediction models to classify the occurrence concentrations of some antibiotics and Carbamazepine, by tree boosting algorithms.…”

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

Comparison of federated learning algorithms. by Duy-Dong Le (22057362)

Data and code resources. by Sam Hall-McMaster (10343795)

Subjects:

File includes code "Transfer learning.R" and "updatebeta.cpp" for implementing transfer learning methods. by Lulu Pan (8977979)

Subjects:

TreeMap 2016 Stand Size Code Algorithm (Image Service) by U.S. Forest Service (17476914)

“…We used a random forests machine-learning algorithm to impute the forest plot data to a set of target rasters provided by Landscape Fire and Resource Management Planning Tools (LANDFIRE: https://landfire.gov). …”

Scripts for GC, CRC, and IBD in Python and R by Animesh Acharjee (6400427)

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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)

Research data for paper: Efficient Event-based Delay Learning in Spiking Neural Networks by Balázs Mészáros (16890225)

“…<p dir="ltr">The data in this repository accompanies the paper 'Efficient Event-based Delay Learning in Spiking Neural Networks'</p><p dir="ltr">The data relates to 4 benchmarks:</p><ol><li>Spiking Heidelberg Digits (SHD).…”

G R code algorithm. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

HaPy-Bug - Bug localization learning to rank algorithm results by Piotr Przymus (14564009)

Code and data. by Shangyang Jin (21772466)

Code used for data analysis in this study. by Nourin Sultana (22339463)

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Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

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

Maple code for algorithm 3. by Peter Thompson (165468)

Figure 2 from DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways by Zhaoxiang Cai (20445441)