Dynamically generated benchmarks with vbench

Category: scikit-learn
#gsoc #vbench #benchmarking #python

To construct a vbench benchmark you need a setup string and a code string. The constructor’s signature is:

Benchmark(self, code, setup, ncalls=None, repeat=3, cleanup=None, name=None, description=None, start_date=None, logy=False).

Why generate benchmarks dynamically?

For most scikit-learn purposes, the code string will be …

Support vector regression on Anscombe’s dataset

Category: scikit-learn
#anscombe #outlier #robust regression #support vector regression #svm #svr #python #scikit-learn

Anscombe’s quartet is a set of four toy datasets that look very different, but many of their statistics coincide. They were developed by Francis Anscombe as a striking visual to show that even for small datasets, blindly examining their statistical properties without considering their structure can mislead.

Anscombe's datasets

Particularly, the …