నిధుల సేకరణ 15 సెప్టెంబర్ 2024 – 1 అక్టోబర్ 2024 నిధులసేకరణ గురించి

Co-Clustering. Models, algorithms and applications.

Co-Clustering. Models, algorithms and applications.

Gérard Govaert, Mohamed Nadif
ఈ పుస్తకం ఎంతగా నచ్చింది?
దింపుకొన్న ఫైల్ నాణ్యత ఏమిటి?
పుస్తక నాణ్యత అంచనా వేయడాలనుకుంటే దీన్ని దింపుకోండి
దింపుకొన్న ఫైళ్ళ నాణ్యత ఏమిటి?
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach.
Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixtures adapted to different types of data. The algorithms used are described and related works with different classical methods are presented and commented upon. This chapter is useful in tackling the problem of
co-clustering under the mixture approach. Chapter 2 is devoted to the latent block model proposed in the mixture approach context. The authors discuss this model in detail and present its interest regarding co-clustering. Various algorithms are presented in a general context. Chapter 3 focuses on binary and categorical data. It presents, in detail, the appropriated latent block mixture models. Variants of these models and algorithms are presented and illustrated using examples. Chapter 4 focuses on contingency data. Mutual information, phi-squared and model-based co-clustering are studied. Models, algorithms and connections among different approaches are described and illustrated. Chapter 5 presents the case of continuous data. In the same way, the different approaches used in the previous chapters are extended to this situation.

Contents

1. Cluster Analysis.
2. Model-Based Co-Clustering.
3. Co-Clustering of Binary and Categorical Data.
4. Co-Clustering of Contingency Tables.
5. Co-Clustering of Continuous Data.

About the Authors

Gérard Govaert is Professor at the University of Technology of Compiègne, France. He is also a member of the CNRS Laboratory Heudiasyc (Heuristic and diagno

వర్గాలు:
సంవత్సరం:
2013
ముద్రణం:
1
ప్రచురణకర్త:
Wiley-ISTE
భాష:
english
పేజీల సంఖ్య:
256
ISBN 10:
1848214731
ISBN 13:
9781848214736
ఫైల్:
PDF, 2.34 MB
IPFS:
CID , CID Blake2b
english, 2013
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