Journal ArticleDOI
Pattern Recognition and Machine Learning
TLDR
This book covers a broad range of topics for regular factorial designs and presents all of the material in very mathematical fashion and will surely become an invaluable resource for researchers and graduate students doing research in the design of factorial experiments.Abstract:
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366.read more
Citations
More filters
Journal ArticleDOI
Leveraging multiviews of trust and similarity to enhance clustering-based recommender systems
TL;DR: This work develops a multiview clustering method through which users are iteratively clustered from the views of both rating patterns and social trust relationships, which can effectively improve both the accuracy and coverage of recommendations as well as in the cold start situation.
Journal ArticleDOI
Pleiotropy and principal components of heritability combine to increase power for association analysis.
TL;DR: An alternative method based on the principal component of heritability (PCH) is developed that uses one portion of the data for training and the remainder for testing, resulting in a powerful test for association.
Journal ArticleDOI
Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters.
Kyall R. Zenger,Mehar S. Khatkar,David B. Jones,Nima Khalilisamani,Nima Khalilisamani,Dean R. Jerry,Herman W. Raadsma,Herman W. Raadsma +7 more
TL;DR: The technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries are discussed, with a particular focus on molluscs and marine shrimp.
Proceedings ArticleDOI
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction
TL;DR: This work proposes Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using auxiliary information such as node similarities.
Journal ArticleDOI
What to do when K-means clustering fails: A simple yet principled alternative algorithm
TL;DR: The simplicity and effectiveness of this algorithm on the health informatics problem of clinical sub-typing in a cluster of diseases known as parkinsonism is demonstrated as well as being statistically rigorous as it is based on nonparametric Bayesian Dirichlet process mixture modeling.