This extension wraps functionality from the Smile library (http://haifengl.github.io/smile/) and provides them as operators.

Smile is a fast and comprehensive machine learning engine. They focus on Speed, Ease of Use, Comprehensive, Natural Language Processing and Mathematics and Statisitcs.

Currently the extension provides the following Operators:

• Anomaly:
  • Gaussian Mixture
• Blending:
  • t-SNE
• Cleansing:
  • Probabilistic Principal Component Analysis (PPCA) 
• Clustering:
  • G-Means
• Models:
  • Parametric Probability Estimator
• Learner:
  • Lasso Regression
  • Random Forest (Smile) (now with classification in 0.4.0)
  • Gradient Boosted Tree (Smile)  (now with classification in 0.4.0)
• Statisitics
  • Compare Distribution (enhanced in 0.4.0)

Changes in 0.6.0 (2021-09-10)

* GMM throws a proper exception if there are missing values.

* GMM is now normalizing the data before fitting. This reduces numerical issues which may occur

* GMM has now several ways of calculating it's anomaly score. The default is negative log likelihood instead of 1/likelihood.

* Changed the way how confidences are calculated in GMM to avoid numerical instability.

* GMM is now reporting it's BIC as a performance measure. * Fixed a bug that you could apply the GMM model to a data set with a different schema and receive missing values. A proper error message is thrown.

Version 0.5 (2021-08-11)

• Reworked the GMM operator. It now:
  • provides cluster model, not a custom model anymore
  •     provides cluster assignments and confidences
  •     provides a score, which is 1/p by default with a setting to change the invert
  •     provides scores for each component of the mixture
  •     has all information about the model as a text output of the model

Version 0.4.1 (2021-04-08)

• Fixed a bug that GMM was not able to handle one-class or unlabeled data even though it was able to do.

Version 0.4.0 (2019-12-18)

• Random Forest (Smile) and Gradient Boosted Trees (Smile) now support Classification.
  • Random Forest Regression (Smile) renamed to Random Forest (Smile)
• Compare Distributions: 
  • Added Kullback-Leibler and Jensen-Shannon as options to compare distributions. They run on a normalized bin version of the distribution.
  • Binning for Chi-Square, KL and JS are done on the superset of the data (i.e. min/max are determined on the superset).
  • A proper error message is thrown if you use Compare Distributions on data with missing values, which is not supported.

Version 0.3.0 (2019-09-11)

• New operator: Compare Distributions
  • test the compatibility of two ExampleSets.
• New operator: Gradient Boosted Tree (Smile)
  • Train a gradient boosted tree for Regression (classification currently not supported)
• Renamed Regression operator folder to Learner
• Major internal code refactoring. This may cause that previously trained models are not applicable anymore.

Version 0.2.0 (2019-07-30)

• Added new operator Random Forest Regression (Smile)
• Added the corresponding Random Forest Model

Version 0.1.0 (2019-02-08)

• Extension release
• New operator Gaussian Mixture
• New operator G-Means 
• New operator Probabilistic Principal Component Analysis 
• New operator Lasso Regression
• Operator t-SNE copied from Operator Toolbox Extension
• Operator Parametric Probability Estimator copied from Operator Toolbox Extension