This page provides the current Release Notes for Intel® Data Analytics Acceleration Library. The notes are categorized by year, from newest to oldest, with individual releases listed within each year.
Click a version to expand it into a summary of new features and changes in that version since the last release, and access the download buttons for the detailed release notes, which include important information, such as pre-requisites, software compatibility, installation instructions, and known issues.
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2018
- Initial Release
Overview:
- Introduced API modifications to streamline library usage and enable consistency across functionality.
- Introduced support for Decision Tree for both classification and regression. The feature includes calculation of Gini index and Information Gain for classification, and mean squared error (MSE) for regression split criteria, and Reduced Error Pruning.
- Introduced support for Decision Forest for both classification and regression. The feature includes calculation of Gini index for classification, variance for regression split criteria, generalization error, and variable importance measures such as Mean Decrease Impurity and Mean Decrease Accuracy.
- Introduced support for varying learning rate in the Stochastic Gradient Descent algorithm for neural network training.
- Introduced support for filtering in the Data Source including loading selected features/columns from CSV data source and binary representation of the categorical features.
- Extended Neural Network layers with Element Wise Add layer.
- Introduced new samples that allow easy integration of the library with Spark* MLlib.
- Introduced service method for enabling thread pinning;Performance improvements in various algorithms on Intel® Xeon® Processor supporting Intel® Advanced Vector Extensions 512 (Intel® AVX-512) (codename Skylake Server).
Known Issues:
- Intel DAAL Python API (a.k.a. pyDAAL) is provided as source. When build it on Windows, users may see warning messages. These warning messages do not indicate critical issues and do not affect the library's functionality.
- Intel DAAL Python API (a.k.a. pyDAAL) built from the source does not work on OS X* El Capitan (version 10.11). Workaround: Users can get the Intel Distribution of Python as an Anaconda package (http://anaconda.org/intel/), which contains a pre-built pyDAAL that works on OS X* El Capitan.