Quickly Score Models (scorer)
A set of tools to quickly score models commonly used to data analysis and data science using uncommon scoring metrics. For example, you might want to use a weighted absolute percent error instead of a root mean square deviation to score that regression model.
Time Series Clustering with Dynamic Time Warping (dtwclust)
Time series clustering using different techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Additionally, an implementation of k-Shape clustering is available.
Distance Metric Learning in R (dml)
The state-of-the-art algorithms for distance metric learning, including global and local methods such as Relevant Component Analysis, Discriminative Component Analysis, Local Fisher Discriminant Analysis, etc. These distance metric learning methods are widely applied in feature extraction, dimensionality reduction, clustering, classification, information retrieval, and computer vision problems.