========================= Comparing implementations ========================= The following benchmarks compare different implementations of the same algorithm. .. contents:: :local: Benchmarks around scikit-learn ============================== .. toctree:: :maxdepth: 1 scikit-learn/gridsearch_cache Some benchmarks are available on :epkg:`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 `_