Download JAR files tagged by fitting with all dependencies

CORS Filter is a universal solution for fitting Cross-Origin Resource Sharing (CORS) support to Java web applications. CORS is a recent W3C effort to introduce a standard mechanism for enabling cross-domain requests in web browsers and participating servers.

This charting library ${project.artifactId}- is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...).

This charting library ${project.artifactId}- is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...).

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

Class for building pace regression linear models and using them for prediction. Under regularity conditions, pace regression is provably optimal when the number of coefficients tends to infinity. It consists of a group of estimators that are either overall optimal or optimal under certain conditions. The current work of the pace regression theory, and therefore also this implementation, do not handle: - missing values - non-binary nominal attributes - the case that n - k is small where n is the number of instances and k is the number of coefficients (the threshold used in this implmentation is 20) For more information see: Wang, Y (2000). A new approach to fitting linear models in high dimensional spaces. Hamilton, New Zealand. Wang, Y., Witten, I. H.: Modeling for optimal probability prediction. In: Proceedings of the Nineteenth International Conference in Machine Learning, Sydney, Australia, 650-657, 2002.