scikit learn 5950X

AMD Ryzen 9 7950X 16-Core testing with a ASUS ROG CROSSHAIR X670E HERO (1101 BIOS) and AMD Radeon RX 7900 XTX 24GB on Ubuntu 22.04 via the Phoronix Test Suite.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2305115-NE-SCIKITLEA14
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Identifier
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Date
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  Test
  Duration
a
May 10 2023
  6 Hours, 55 Minutes
b
May 10 2023
  6 Hours, 16 Minutes
c
May 11 2023
  6 Hours, 24 Minutes
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  6 Hours, 32 Minutes

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scikit learn 5950X Suite 1.0.0 System Test suite extracted from scikit learn 5950X. pts/scikit-learn-2.0.0 plot_omp_lars.py Benchmark: Plot OMP vs. LARS pts/scikit-learn-2.0.0 lasso.py Benchmark: Lasso pts/scikit-learn-2.0.0 sgd_regression.py Benchmark: SGD Regression pts/scikit-learn-2.0.0 glm.py Benchmark: GLM pts/scikit-learn-2.0.0 online_ocsvm.py Benchmark: SGDOneClassSVM pts/scikit-learn-2.0.0 plot_lasso_path.py Benchmark: Plot Lasso Path pts/scikit-learn-2.0.0 hist_gradient_boosting_higgsboson.py Benchmark: Hist Gradient Boosting Higgs Boson pts/scikit-learn-2.0.0 isolation_forest.py Benchmark: Isolation Forest pts/scikit-learn-2.0.0 tree.py Benchmark: Tree pts/scikit-learn-2.0.0 20newsgroups.py -e logistic_regression Benchmark: 20 Newsgroups / Logistic Regression pts/scikit-learn-2.0.0 plot_neighbors.py Benchmark: Plot Neighbors pts/scikit-learn-2.0.0 feature_expansions.py Benchmark: Feature Expansions pts/scikit-learn-2.0.0 hist_gradient_boosting_threading.py Benchmark: Hist Gradient Boosting Threading pts/scikit-learn-2.0.0 hist_gradient_boosting_adult.py Benchmark: Hist Gradient Boosting Adult pts/scikit-learn-2.0.0 tsne_mnist.py Benchmark: TSNE MNIST Dataset pts/scikit-learn-2.0.0 plot_fastkmeans.py Benchmark: Plot Fast KMeans pts/scikit-learn-2.0.0 plot_ward.py Benchmark: Plot Ward pts/scikit-learn-2.0.0 text_vectorizers.py Benchmark: Text Vectorizers pts/scikit-learn-2.0.0 mnist.py Benchmark: MNIST Dataset pts/scikit-learn-2.0.0 random_projections.py --n-times 100 Benchmark: Sparse Random Projections / 100 Iterations pts/scikit-learn-2.0.0 hist_gradient_boosting_categorical_only.py Benchmark: Hist Gradient Boosting Categorical Only pts/scikit-learn-2.0.0 hist_gradient_boosting.py Benchmark: Hist Gradient Boosting pts/scikit-learn-2.0.0 isotonic.py --iterations 100 --log_min_problem_size 1 --log_max_problem_size 10 --dataset logistic Benchmark: Isotonic / Logistic pts/scikit-learn-2.0.0 sample_without_replacement.py Benchmark: Sample Without Replacement pts/scikit-learn-2.0.0 plot_hierarchical.py Benchmark: Plot Hierarchical pts/scikit-learn-2.0.0 covertype.py Benchmark: Covertype Dataset Benchmark pts/scikit-learn-2.0.0 sparsify.py Benchmark: Sparsify pts/scikit-learn-2.0.0 lof.py Benchmark: LocalOutlierFactor pts/scikit-learn-2.0.0 saga.py Benchmark: SAGA pts/scikit-learn-2.0.0 plot_polynomial_kernel_approximation.py Benchmark: Plot Polynomial Kernel Approximation pts/scikit-learn-2.0.0 plot_svd.py Benchmark: Plot Singular Value Decomposition pts/scikit-learn-2.0.0 kernel_pca_solvers_time_vs_n_components.py Benchmark: Kernel PCA Solvers / Time vs. N Components pts/scikit-learn-2.0.0 kernel_pca_solvers_time_vs_n_samples.py Benchmark: Kernel PCA Solvers / Time vs. N Samples pts/scikit-learn-2.0.0 plot_nmf.py Benchmark: Plot Non-Negative Matrix Factorization pts/scikit-learn-2.0.0 isotonic.py --iterations 100 --log_min_problem_size 1 --log_max_problem_size 10 --dataset perturbed_logarithm Benchmark: Isotonic / Perturbed Logarithm pts/scikit-learn-2.0.0 rcv1_logreg_convergence.py Benchmark: RCV1 Logreg Convergencet pts/scikit-learn-2.0.0 isotonic.py --iterations 100 --log_min_problem_size 1 --log_max_problem_size 10 --dataset pathological Benchmark: Isotonic / Pathological pts/scikit-learn-2.0.0 plot_parallel_pairwise.py Benchmark: Plot Parallel Pairwise pts/scikit-learn-2.0.0 plot_incremental_pca.py Benchmark: Plot Incremental PCA pts/scikit-learn-2.0.0 glmnet.py Benchmark: Glmnet