4 papers
Statistical Properties of -means Clustering for Data Missing Completely at Random
Xin Guan
The classical -means clustering cannot be directly used to incomplete data, and existing -means-based clustering for missing data primarily focus on improving the practical a…
MNAR--means: A -means Clustering for Data Missing Not at Random with Magnitude-Decaying Probability
Xin Guan
The classical -means clustering, based on distances computed from all data features, cannot be directly applied to incomplete data with missing values. A natural extension of $k…
Regularized k-POD: Sparse k-means clustering for high-dimensional missing data
Xin Guan, Yoshikazu Terada
The classical k-means clustering, based on distances computed from all data features, cannot be directly applied to incomplete data with missing values. A natural extension of k-me…
Some notes on the -means clustering for missing data
Yoshikazu Terada, Xin Guan
The classical -means clustering requires a complete data matrix without missing entries. As a natural extension of the -means clustering for missing data, the -POD cluster…