Code and data for the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms" حسب Noelle Madyson Daigle (22120114)

"…<p dir="ltr">Code and data for analysis detailed in the paper "Investigating machine learning algorithms to classify label-free images of pancreatic neuroendocrine neoplasms." …"

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code حسب Goutami Sooda (20714729)

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

Machine learning algorithm performance evaluated by ROC curves. حسب Man Wang (110466)

Machine learning from 21 gly - DEGs filter core gene. حسب Ziyang Liu (242055)

Performance of various biclustering algorithms on FilmTrust dataset with Q-learning. حسب Muhammad Waqar (500788)

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

The parameter setting of the evolutionary neural network. حسب Wenbing Shi (5806160)

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Performance of various biclustering algorithms on ML-100K dataset with Q- learning. حسب Muhammad Waqar (500788)

الموضوعات:

Performance of various biclustering algorithms on ML-latest-small dataset with Q-learning. حسب Muhammad Waqar (500788)

الموضوعات:

The genome coding scheme. حسب Wenbing Shi (5806160)

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The optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Optimal number of clusters identified using the GMM clustering algorithm. حسب Dinh K. Tang (20469082)

Impact of multiunit merging on neural information encoding. حسب Daniel Suárez-Barrera (22676654)

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rbpTransformer model using multiple cores. حسب Ahmet Gürhanlı (21602042)

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Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>" حسب Yize Wang (19535173)

"…<p dir="ltr">Codes for "<b>A coherent power-load optimization algorithm for wind-farm-level yaw control considering wake effects via deep neural network</b>"</p>…"

Evaluation metrics with Q-learning on ML-latest-small. حسب Muhammad Waqar (500788)

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code_4 حسب Olga Ovtsarenko (20432033)

Data and code availability: Machine Learning on systematically curated data reveals key determinants of magnetic hyperthermia performance حسب Edgar Vega (21981590)

"…The CatBoost algorithm emerged as the most effective model, achieving the lowest mean absolute error (20.92 W/g) and root mean squared error (39.41 W/g), along with a high coefficient of determination (R² = 0.98). …"

Agent learning of FilmTrust dataset across various parameters. حسب Muhammad Waqar (500788)

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