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#### 1Antonio Gulli's coding playground: DBSCAN clustering algorithm

Here you have a DBSCAN code implemented in C++, boost and stl
8 years ago by @cdevries
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#### 1Consensus clustering - Wikipedia, the free encyclopedia

Consensus clustering has emerged as an important elaboration of the classical clustering problem. Consensus clustering, also called aggregation of clustering (or partitions), refers to the situation in which a number of different (input) clusterings have been obtained for a particular dataset and it is desired to find a single (consensus) clustering which is a better fit in some sense than the existing clusterings. Consensus clustering is thus the problem of reconciling clustering information about the same data set coming from different sources or from different runs of the same algorithm. When cast as an optimization problem, consensus clustering is known as median partition, and has been shown to be NP-complete.
8 years ago by @cdevries
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#### 1InformIT: Expectation-Maximization Theory > Introduction

EM has been shown to have favorable convergence properties, automatical satisfaction of constraints, and fast convergence. The next section explains the traditional approach to deriving the EM algorithm and proving its convergence property. Section 3.3 covers the interpretion the EM algorithm as the maximization of two quantities: the entropy and the expectation of complete-data likelihood. Then, the K-means algorithm and the EM algorithm are compared. The conditions under which the EM algorithm is reduced to the K-means are also explained. The discussion in Section 3.4 generalizes the EM algorithm described in Sections 3.2 and 3.3 to problems with partial-data and hidden-state. We refer to this new type of EM as the doubly stochastic EM. Finally, the chapter is concluded in Section 3.5.
8 years ago by @cdevries
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#### 1MCL - an algorithm for clustering graphs

The MCL algorithm is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for graphs based on simulation of (stochastic) flow in graphs.
9 years ago by @cdevries
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#### 1Clustering Papers

A list of cluster papers. Includes some links to source code.
9 years ago by @cdevries
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#### 1Partitioning Around Medoids (PAM)

Compare k-means and PAM. PAM is also known as k-medoids.
9 years ago by @cdevries
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#### 1Lecture 4: Clustering

Useful bullet points on different types of clustering.
9 years ago by @cdevries
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#### 1Parallel Spectral Clustering

This tool performs spectral clustering using either sparse similarity matrix (nearest neighbors) or the Nystrom method.
9 years ago by @cdevries
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#### 3On Quantitative Evaluation of Clustering Systems

, , , and . Kluwer Academic Publishers, (2003)
6 years ago by @cdevries
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#### 1Classifying Clustering Schemes

, and . (2010)cite arxiv:1011.5270.
6 years ago by @cdevries
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#### 1On using class-labels in evaluation of clusterings

MultiClust: 1st International Workshop on Discovering, Summarizing and Using Multiple Clusterings Held in Conjunction with KDD 2010, Washington, DC, (2010)
6 years ago by @cdevries
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#### 1K-means clustering: A half-century synthesis

British Journal of Mathematical and Statistical Psychology 59 (1): 1--34 (2006)
6 years ago by @cdevries
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#### 2Clustering via Hilbert space

Physica A: Statistical Mechanics and its Applications 302 (1-4): 70--79 (2001)
7 years ago by @cdevries
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#### 3An Entropy Weighting k-Means Algorithm for Subspace Clustering of High-Dimensional Sparse Data

, , and . IEEE Transactions on Knowledge and Data Engineering 19 (8): 1026-1041 (2007)
7 years ago by @cdevries
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#### 1Topic-based Index Partitions for Efficient and Effective Selective Search

, and . Large-Scale Distributed Systems for Information Retrieval (2010)
7 years ago by @cdevries
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#### 4Recent trends in hierarchic document clustering: a critical review

Information Processing & Management 24 (5): 577--597 (1988)
7 years ago by @cdevries
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#### 2The effectiveness of query-specific hierarchic clustering in information retrieval

Information processing & management 38 (4): 559--582 (2002)
7 years ago by @cdevries
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#### 2Testing the cluster hypothesis in distributed information retrieval

, and . Information Processing & Management 42 (5): 1137--1150 (2006)
7 years ago by @cdevries
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#### 4Evaluating document clustering for interactive information retrieval

CIKM '01: Proceedings of the tenth international conference on Information and knowledge management, page 33--40. New York, NY, USA, ACM, (2001)
7 years ago by @cdevries
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#### 2Using Text Segmentation to Enhance the Cluster Hypothesis

Artificial Intelligence: Methodology, Systems, and Applications (2008)
7 years ago by @cdevries
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#### 1A model of cluster searching based on classification

Information systems 5 (3): 189--195 (1980)
7 years ago by @cdevries
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#### 2Recent advances in cluster analysis

, and . International Journal of Intelligent Computing and Cybernetics 1 (4): 484--508 (2008)
7 years ago by @cdevries
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#### 2Evaluating text representations for retrieval of the best group of documents

, and . ECIR'08: Proceedings of the IR research, 30th European conference on Advances in information retrieval, page 454--462. Berlin, Heidelberg, Springer-Verlag, (2008)
7 years ago by @cdevries
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