Scikit-Learn

Scikit-learn is a Python module for machine learning built on NumPy, SciPy, and is BSD-licensed.

To run this test with the Phoronix Test Suite, the basic command is: phoronix-test-suite benchmark scikit-learn.

Performance Metrics

Scikit-Learn 1.1.3

Benchmark: Sparse Random Projections, 100 Iterations

OpenBenchmarking.org metrics for this test profile configuration based on 142 public results since 20 November 2022 with the latest data as of 10 October 2023.

Below is an overview of the generalized performance for components where there is sufficient statistically significant data based upon user-uploaded results. It is important to keep in mind particularly in the Linux/open-source space there can be vastly different OS configurations, with this overview intended to offer just general guidance as to the performance expectations.

Based on OpenBenchmarking.org data, the selected test / test configuration (Scikit-Learn 1.1.3 - Benchmark: Sparse Random Projections, 100 Iterations) has an average run-time of 16 minutes. By default this test profile is set to run at least 3 times but may increase if the standard deviation exceeds pre-defined defaults or other calculations deem additional runs necessary for greater statistical accuracy of the result.

Based on public OpenBenchmarking.org results, the selected test / test configuration has an average standard deviation of 0.1%.

Tested CPU Architectures

This benchmark has been successfully tested on the below mentioned architectures. The CPU architectures listed is where successful OpenBenchmarking.org result uploads occurred, namely for helping to determine if a given test is compatible with various alternative CPU architectures.