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Found 6 papers, 1 papers with code
Regularized K-means through hard-thresholding
We study a framework of regularized $K$-means methods based on direct penalization of the size of the cluster centers.
Robust Clustering Using Tau-Scales
K means is a popular non-parametric clustering procedure introduced by Steinhaus (1956) and further developed by MacQueen (1967).
Computation 62G35, 62H30, 62H35
Regression Phalanxes
Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems.
Ensembles of phalanxes across assessment metrics for robust ranking of homologous proteins
Our approach uses an ensemble of models in a classifier and an ensemble of assessment metrics.
Multi-rank Sparse Hierarchical Clustering
There has been a surge in the number of large and flat data sets - data sets containing a large number of features and a relatively small number of observations - due to the growing ability to collect and store information in medical research and other fields.
Ensembling classification models based on phalanxes of variables with applications in drug discovery
Because the class of interest is rare in the training data, there is relatively little information in the known class response labels for model building.
