Today I am very excited to announce that Smile 1.1 is released! Among many improvements, we get the new high level Scala API, interactive Shell, and a nice project website with programming guides, API doc, etc.!
With Smile 1.1, data scientists can develop advanced models with high level Scala operators in the Shell and developers can deploy them immediately in the app. That is, data scientists and developers can speak the same language now! Continue reading →
I have been developing a comprehensive machine learning library of advanced algorithms, called SMILE (Statistical Machine Intelligence and Learning Engine), for several years with my spare time. Today I am very pleased to announce that SMILE is now available on GitHub under Apache 2.0 license. SMILE is self contained and requires only the standard Java library. With advanced data structures and learning algorithms, SMILE achieves the state of the art of performance.
Classification: Support Vector Machines, Decision Trees, AdaBoost, Gradient Boosting, Random Forest, Logistic Regression, Neural Networks, RBF Networks, Maximum Entropy Classifier, KNN, Naïve Bayesian, Fisher/Linear/Quadratic/Regularized Discriminant Analysis.
Regression: Support Vector Regression, Gaussian Process, Regression Trees, Gradient Boosting, Random Forest, RBF Networks, OLS, LASSO, Ridge Regression.
Feature Selection: Genetic Algorithm based Feature Selection, Ensemble Learning based Feature Selection, Signal Noise ratio, Sum Squares ratio.
SMILE is well documented and you can browse the javadoc for more information.
SMILE also has a Swing-based data visualization library SmilePlot, which provides scatter plot, line plot, staircase plot, bar plot, box plot, histogram, 3D histogram, dendrogram, heatmap, hexmap, qq plot, contour plot, surface, and wireframe. The class PlotCanvas provides builtin functions such as zoom in/out, export, print, customization, etc.
SmilePlot requires SwingX library for JXTable. But if your environment cannot use SwingX, it is easy to remove this dependency by using JTable.