Download nz.ac.waikato.cms.weka.thirdparty JAR files with all dependencies

Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors. For more information, see Alexander Genkin, David D. Lewis, David Madigan (2004). Large-scale bayesian logistic regression for text categorization.

Java client for the Zendesk API

The Waikato Environment for Knowledge Analysis (WEKA), a machine learning workbench. This is the stable version. Apart from bugfixes, this version does not receive any other updates.

Java library for analyzing the classpath of an application, used to determine class hierarchies.

This package currently contains classes for training multilayer perceptrons with one hidden layer, where the number of hidden units is user specified. MLPClassifier can be used for classification problems and MLPRegressor is the corresponding class for numeric prediction tasks. The former has as many output units as there are classes, the latter only one output unit. Both minimise a penalised squared error with a quadratic penalty on the (non-bias) weights, i.e., they implement "weight decay", where this penalised error is averaged over all training instances. The size of the penalty can be determined by the user by modifying the "ridge" parameter to control overfitting. The sum of squared weights is multiplied by this parameter before added to the squared error. Both classes use BFGS optimisation by default to find parameters that correspond to a local minimum of the error function. but optionally conjugated gradient descent is available, which can be faster for problems with many parameters. Logistic functions are used as the activation functions for all units apart from the output unit in MLPRegressor, which employs the identity function. Input attributes are standardised to zero mean and unit variance. MLPRegressor also rescales the target attribute (i.e., "class") using standardisation. All network parameters are initialised with small normally distributed random values.

A wrapper class for the liblinear tools (the liblinear classes, typically the jar file, need to be in the classpath to use this classifier). Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin (2008). LIBLINEAR - A Library for Large Linear Classification.

There is now an xjc plugin that automatically generates the toString(), hashCode() and equals(Object) methods using jakarta-common-lang's ToStringBuilder, HashCodeBuilder and EqualsBuilder

When generating XML schema from Java source code using the schemagen tool a common approach is to use the @XmlElementWrapper and @XmlElement annotations to handle schema generation for collections. However, when generating Java source from a schema using the xjc tool the resulting code is not created with these annotations. Instead, the generated Java source contains "injected" inner classes to accommodate the collection of elements contained within an element.

k-means clustering with automatic selection of k. Restarts k-means and selects the best k using the Calinski and Harabasz criterion, without cross-validation.

Java library for analyzing the classpath of an application, used to determine class hierarchies.

This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs.

This is the tonic look-and-feel packaged to be distributed with the SQuirreLSQL client. This pluggable look and feel is a free substitute for the default native look and feel of Swing, 'Metal', distributed under the GNU Lesser General Public License. Metal lacks both in usability and aesthetics. It contains considerable graphical noise, distracting the user from the key elements of the GUI. Tonic, on the other hand, tries to provide a clean, balanced look and an improved feel. Tonic is available free of charge both for commercial and non-commercial applications. It lends a professional touch and a very tidy and clean interface to your Swing based applications.

Pulls down protobuf, patches it, compiles, and then relocates/shades.