Novel centroid selection approaches for KMeans-clustering based recommender systems
Recommender systems have the ability to filter unseen information for predicting whether a
particular user would prefer a given item when making a choice. Over the years, this process …
particular user would prefer a given item when making a choice. Over the years, this process …
K-means clustering algorithm with improved initial center
Z Chen, S ** similar data into a set of clusters. Cluster analysis is
one of the major data analysis techniques and k-means one of the most popular partitioning …
one of the major data analysis techniques and k-means one of the most popular partitioning …
A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network
Background Genetic interaction profiles are highly informative and helpful for understanding
the functional linkages between genes, and therefore have been extensively exploited for …
the functional linkages between genes, and therefore have been extensively exploited for …
Seed selection algorithm through K-means on optimal number of clusters
Clustering is one of the important unsupervised learning in data mining to group the similar
features. The growing point of the cluster is known as a seed. To select the appropriate seed …
features. The growing point of the cluster is known as a seed. To select the appropriate seed …
[HTML][HTML] Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset
Human neuromagnetic activity is characterised by a complex combination of transient bursts
with varying spatial and temporal characteristics. The characteristics of these transient bursts …
with varying spatial and temporal characteristics. The characteristics of these transient bursts …
A transfer learning approach via procrustes analysis and mean shift for cancer drug sensitivity prediction
T Turki, Z Wei, JTL Wang - Journal of bioinformatics and …, 2018 - World Scientific
Transfer learning (TL) algorithms aim to improve the prediction performance in a target task
(eg the prediction of cisplatin sensitivity in triple-negative breast cancer patients) via …
(eg the prediction of cisplatin sensitivity in triple-negative breast cancer patients) via …