Showing 7 of total 7 results (show query)
kisungyou
T4cluster:Tools for Cluster Analysis
Cluster analysis is one of the most fundamental problems in data science. We provide a variety of algorithms from clustering to the learning on the space of partitions. See Hennig, Meila, and Rocci (2016, ISBN:9781466551886) for general exposition to cluster analysis.
Maintained by Kisung You. Last updated 4 years ago.
6 stars 4.26 score 9 scripts 2 dependents
rcurtin
mlpack:'Rcpp' Integration for the 'mlpack' Library
A fast, flexible machine learning library, written in C++, that aims to provide fast, extensible implementations of cutting-edge machine learning algorithms. See also Curtin et al. (2023) <doi:10.21105/joss.05026>.
Maintained by Ryan Curtin. Last updated 4 months ago.
3.71 score 20 scripts 8 dependents
lmjl-alea
squat:Statistics for Quaternion Temporal Data
An implementation of statistical tools for the analysis of rotation-valued time series and functional data. It relies on pre-existing quaternion data structure provided by the 'Eigen' 'C++' library.
Maintained by Aymeric Stamm. Last updated 1 years ago.
2 stars 3.00 score 6 scripts
ediu3095
clustlearn:Learn Clustering Techniques Through Examples and Code
Clustering methods, which (if asked) can provide step-by-step explanations of the algorithms used, as described in Ezugwu et. al., (2022) <doi:10.1016/j.engappai.2022.104743>; and datasets to test them on, which highlight the strengths and weaknesses of each technique, as presented in the clustering section of 'scikit-learn' (Pedregosa et al., 2011) <https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>.
Maintained by Eduardo Ruiz Sabajanes. Last updated 2 years ago.
1 stars 2.70 score 4 scripts
sheikhi-a
MajKMeans:k-Means Algorithm with a Majorization-Minimization Method
A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package 'MajKMeans' are cluster_km() and cluster_MajKm(). cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering.
Maintained by Sheikhi Ayyub. Last updated 1 years ago.
2.00 score
cran
Kira:Machine Learning
Machine learning, containing several algorithms for supervised and unsupervised classification, in addition to a function that plots the Receiver Operating Characteristic (ROC) and Precision-Recall (PRC) curve graphs, and also a function that returns several metrics used for model evaluation, the latter can be used in ranking results from other packs.
Maintained by Paulo Cesar Ossani. Last updated 7 months ago.
1.70 scoresheikhi-a
MajMinKmeans:k-Means Algorithm with a Majorization-Minimization Method
A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package 'MajMinKmeans' are cluster_km() and cluster_MajKm(). Cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering. Another useful function is MajMinOptim(), which helps to find the optimum values of the Majorization-Minimization estimator.
Maintained by Sheikhi Ayyub. Last updated 11 months ago.
1.00 score