daal4py 2020.1
Introduced new functionality:
- Elastic Net algorithm with L1 and L2 regularization in batch computation mode. The algorithm supports various optimization solvers that handle non-smooth functions.
- Probabilistic classification for Decision Forest Classification algorithm with a choice voting method to calculate probabilities.
Extended existing functionality:
- Performance optimizations for distributed Spark samples, K-means algorithm for some input dimensions, Gradient Boosted Trees training stage for large datasets on multi-core platforms and Decision Forest prediction stage for datasets with a small number of observations on processors that support Intel® Advanced Vector Extensions 2 (Intel® AVX2) and Intel® Advanced Vector Extensions 512 (Intel® AVX-512)
- Performance optimizations across algorithms that use SOA (Structure Of Arrays) NumericTable as an input on processors that support Intel® Advanced Vector Extensions 512 (Intel® AVX-512)