Kristina P. Sinaga

A lifelong learner and not a people pleaser 😀

Unsupervised multiview fuzzy c-means clustering algorithm

The rapid development in information technology makes it easier to collect vast numbers of data through the cloud, internet and other sources of information. Multiview clustering is a significant...

Posted by Kristina on March 14, 2024

Entropy k-means clustering with feature reduction under unknown number of clusters

The k-means algorithm with its extensions is the most used clustering method in the literature. But, the k-means and its various extensions are generally affected by initializations with a given ...

Posted by Kristina on March 14, 2024

Collaborative feature-weighted multi-view fuzzy c-means clustering

Fuzzy c-means (FCM) clustering had been extended for handling multi-view data with collaborative idea. However, these collaborative multi-view FCM treats multi-view data under equal importance of...

Posted by Kristina on March 14, 2024

Modified relational mountain clustering method

The relational mountain clustering method (RMCM) is a simple and effective algorithm that can be used to obtain cluster centers and partitions for a relational data set. However, the performance ...

Posted by Kristina on March 14, 2024

A feature-reduction multi-view k-means clustering algorithm

The k-means clustering algorithm is the oldest and most known method in cluster analysis. It has been widely studied with various extensions and applied in a variety of substantive areas. Since i...

Posted by Kristina on March 14, 2024

Unsupervised k-means clustering algorithm

We propose a novel unsupervised k-means (U-k-means) clustering algorithm with automatically finding an optimal number of clusters without giving any initialization and parameter selection. The co...

Posted by Kristina on March 13, 2024