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BARMPy: Bayesian Additive Regression Models Python Package
Van Boxel, Danielle
regAL: Python Package for Active Learning of Regression Problems
Surzhikova, Elizaveta ; Proppe, Jonny
milearn: A Python Package for Multi-Instance Machine Learning
Zankov, Dmitry ; Polishchuk, Pavlo ; Sobieraj, Michal ; et al.
Algorithms and Scientific Software for Quasi-Monte Carlo, Fast Gaussian Process Regression, and Scientific Machine Learning
Sorokin, Aleksei G.
Comprehensive analysis of ship detention probabilities using binary logistic regression method with machine learning
Hocek, Hürol ; Yay, Sefa ; Yazir, Devran
In Ocean Engineering 1 January 2025 315
BARMPy: Bayesian additive regression models Python package.
Van Boxel, Danielle
Computational Statistics. Jun2025, Vol. 40 Issue 5, p2807-2824. 18p.
Who Wins the Race? (R Vs Python) - An Exploratory Study on Energy Consumption of Machine Learning Algorithms
Chattaraj, Rajrupa ; Chimalakonda, Sridhar ; Sharma, Vibhu Saujanya ; et al.
Teaching Business Analytics Students Logistic Regression Using Python and R.
Li, Min
Business Education Innovation Journal. Jun2023, Vol. 15 Issue 1, p35-41. 7p.
AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning
Alizadeh, Morteza ; Oveisi, Mehrdad ; Falahati, Sonya ; et al.
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning
Liu, Jiashuo ; Wang, Tianyu ; Lam, Henry ; et al.
SuSi: Supervised Self-Organizing Maps for Regression and Classification in Python
Riese, Felix M. ; Keller, Sina
c-lasso -- a Python package for constrained sparse and robust regression and classification
Simpson, Léo ; Combettes, Patrick L. ; Müller, Christian L.
shapr: Explaining Machine Learning Models with Conditional Shapley Values in R and Python
Jullum, Martin ; Olsen, Lars Henry Berge ; Lachmann, Jon ; et al.
Medical artificial intelligence toolbox (MAIT): an explainable machine learning framework for binary classification, survival modelling, and regression analyses
Marandi, Ramtin Zargari ; Frahm, Anne Svane ; Lundgren, Jens ; et al.
Practical Machine Learning
Nyamawe, Ally S. ; Mjahidi, Mohamedi M. ; Nnko, Noe E. ; et al.
ml_edm package: a Python toolkit for Machine Learning based Early Decision Making
Renault, Aurélien ; Achenchabe, Youssef ; Bertrand, Édouard ; et al.
Machine Learning-Based Cardiovascular Disease Prediction: A Comparative Analysis of Classification Algorithms for Enhanced Diagnostic Accuracy
Singh, Harsheeta ; Satija, Vanshaj ; K, Priyadharshini
2025 International Conference on Visual Analytics and Data Visualization (ICVADV) Visual Analytics and Data Visualization (ICVADV), 2025 International Conference on. :1384-1391 Mar, 2025
Efficient Solvers for SLOPE in R, Python, Julia, and C++
Larsson, Johan ; Bogdan, Malgorzata ; Grzesiak, Krystyna ; et al.