Download JAR files tagged by 2007 with all dependencies

ISO 13616-1:2007 specifies the elements of an international bank account number (IBAN) used to facilitate the processing of data internationally in data interchange, in financial environments as well as within and between other industries. The IBAN is designed for automated processing, but can also be used conveniently in other media interchange when appropriate (e.g. paper document exchange, etc.). ISO 13616-1:2007 does not specify internal procedures, file organization techniques, storage media, languages, etc. to be used in its implementation, nor is it designed to facilitate the routing of messages within a network. It is applicable to the textual data which might be conveyed through a system (network). This project provides a general purpose ISO 13616-1:2007 compatible IBAN Java class.

Class for building a best-first decision tree classifier. This class uses binary split for both nominal and numeric attributes. For missing values, the method of 'fractional' instances is used. For more information, see: Haijian Shi (2007). Best-first decision tree learning. Hamilton, NZ. Jerome Friedman, Trevor Hastie, Robert Tibshirani (2000). Additive logistic regression : A statistical view of boosting. Annals of statistics. 28(2):337-407.

Implements the stochastic variant of the Pegasos (Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et al. (2007). This implementation globally replaces all missing values and transforms nominal attributes into binary ones. It also normalizes all attributes, so the coefficients in the output are based on the normalized data. Can either minimize the hinge loss (SVM) or log loss (logistic regression). For more information, see S. Shalev-Shwartz, Y. Singer, N. Srebro: Pegasos: Primal Estimated sub-GrAdient SOlver for SVM. In: 24th International Conference on MachineLearning, 807-814, 2007.