Cluster 1.3.3

Cluster 1.3.2

Cluster 1.3.1

Cluster 1.3.0

Cluster 1.2.9

Cluster 1.2.8

Cluster 1.2.7

ClusterR 1.2.6

ClusterR 1.2.5

ClusterR 1.2.4

ClusterR 1.2.3

ClusterR 1.2.2

ClusterR 1.2.1

ClusterR 1.2.0

ClusterR 1.1.9

ClusterR 1.1.8

ClusterR 1.1.7

ClusterR 1.1.6

ClusterR 1.1.5

As of version 1.1.5 the ClusterR functions can take tibble objects as input too.

ClusterR 1.1.4

I modified the ClusterR package to a cpp-header-only package to allow linking of cpp code between Rcpp packages. See the update of the README.md file (16-08-2018) for more information.

ClusterR 1.1.3

I updated the example section of the documentation by replacing the optimal_init with the kmeans++ initializer

ClusterR 1.1.2

ClusterR 1.1.1

ClusterR 1.1.0

ClusterR 1.0.9

ClusterR 1.0.8

ClusterR 1.0.7

I modified the kmeans_miniBatchKmeans_GMM_Medoids.cpp file in the following lines in order to fix the clang-ASAN errors (without loss in performance):

I modified the following functions in the clustering_functions.R file:

ClusterR 1.0.6

The normalized variation of information was added in the external_validation function (https://github.com/mlampros/ClusterR/pull/1)

ClusterR 1.0.5

I fixed the valgrind memory errors

ClusterR 1.0.4

I removed the warnings, which occured during compilation. I corrected the UBSAN memory errors which occured due to a mistake in the check_medoids() function of the utils_rcpp.cpp file. I also modified the quantile_init_rcpp() function of the utils_rcpp.cpp file to print a warning if duplicates are present in the initial centroid matrix.

ClusterR 1.0.3

ClusterR 1.0.2

I modified the RcppArmadillo functions so that ClusterR passes the Windows and OSX OS package check results

ClusterR 1.0.1

I modified the RcppArmadillo functions so that ClusterR passes the Windows and OSX OS package check results

ClusterR 1.0.0