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pypi.org : psevencore
pSeven Core is an integrated toolkit for design space exploration, optimization, and predictive modeling.
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purl: pkg:pypi/psevencore
Keywords: adaptive design, adaptive doe, approximation, approximation model, approximation modeling, approximator, box-behnken, correlation analysis, design exploration, design of experiments, design optimization, design space, difference approximation, dimension reduction, doe, engineering, engineering optimization, feature importance, feature scoring, feature selection, fmi, fmu, fractional factorial, gaussian processes, gradient optimization, kendall, latin hypercube sampling, low discrepancy sequence, mixed integer, mixture of approximators, modeling, multiple fidelity, mutual information, optimization, optimizer, orthogonal array, parametric study, pearson, predictive modeling, principal component analysis, regression, regression tree, response surface, robust optimization, screening index, screening indices, sensitivity analysis, shap, shapley additive explanations, sobol index, sobol indices, spearman, surrogate based optimization, taguchi index, taguchi indices, tensor approximation, variable fidelity, deep-learning, explainability, gradient-boosting, interpretability, machine-learning, shapley
License: Other
Latest release: about 2 months ago
First release: 4 months ago
Downloads: 114 last month
Stars: 21,543 on GitHub
Forks: 3,156 on GitHub
Total Commits: 2013
Committers: 239
Average commits per author: 8.423
Development Distribution Score (DDS): 0.775
More commit stats: commits.ecosyste.ms
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Last synced: 20 days ago