The SVR Path Algorithm (svrpath)
Computes the entire solution paths for Support Vector Regression with low cost. See Wang, G. et al (2008) <doi:10.1109/TNN.2008.2002077> for details regarding the method.

Evaluation Metrics for Customer Scoring Models Depending on Binary Classifiers (CustomerScoringMetrics)
Functions for evaluating and visualizing predictive model performance (specifically: binary classifiers) in the field of customer scoring. These metrics include lift, lift index, gain percentage, top-decile lift, F1-score, expected misclassification cost and absolute misclassification cost. See Berry & Linoff (2004, ISBN:0-471-47064-3), Witten and Frank (2005, 0-12-088407-0) and Blattberg, Kim & Neslin (2008, ISBN:978-0-387-72578-9) for details. Visualization functions are included for lift charts and gain percentage charts. All metrics that require class predictions offer the possibility to dynamically determine cutoff values for transforming real-valued probability predictions into class predictions.

Radiomic’ Image Processing Toolbox (radiomics)
Functions to extract first and second order statistics from images.