Comparing implementations

The following benchmarks compare different implementations of the same algorithm.

Benchmarks around scikit-learn

• Caching algorithm for a GridSearchCV

Some benchmarks are available on PolynomialFeatures at Benchmark of PolynomialFeatures + partialfit of SGDClassifier.

Benchmarks of toy implementations in C++, Python

The following benchmarks were implemented in other repositories. The first one measures differents way to write the dot product in C++ using a couple of processors optimization such as branching or AVX instructions.

• Measures branching in C++ from python

• Measures a vector sum with different accumulator type

The second one looks into the implementation of a logistic regression with python, C++ or C++ optimization provided by other libraries.

• Optimisation de code avec cffi, numba, cython

The next benchmark compares the gain obtained by playing a criterion for decision tree regressor.

• Custom Criterion for DecisionTreeRegressor