Displaying similar documents to “On a method of ordering and clustering of objects”

An alternative extension of the k-means algorithm for clustering categorical data

Ohn San, Van-Nam Huynh, Yoshiteru Nakamori (2004)

International Journal of Applied Mathematics and Computer Science

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Most of the earlier work on clustering has mainly been focused on numerical data whose inherent geometric properties can be exploited to naturally define distance functions between data points. Recently, the problem of clustering categorical data has started drawing interest. However, the computational cost makes most of the previous algorithms unacceptable for clustering very large databases. The -means algorithm is well known for its efficiency in this respect. At the same time, working...

Building a knowledge base for correspondence analysis.

M.ª Carmen Bravo Llatas (1994)

Qüestiió

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This paper introduces a statistical strategy for Correspondence Analysis. A formal description of the choices, actions and decisions taken during data analysis is built. Rules and heuristics have been obtained from the application of this technique to real case studies. The strategy proposed checks suitability of certain types of data matrices for this analysis and also considers a guidance and interpretation of the application of this technique. Some algorithmic-like rules...

Hierarchical text categorization using fuzzy relational thesaurus

Domonkos Tikk, Jae Dong Yang, Sun Lee Bang (2003)

Kybernetika

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Text categorization is the classification to assign a text document to an appropriate category in a predefined set of categories. We present a new approach for the text categorization by means of Fuzzy Relational Thesaurus (FRT). FRT is a multilevel category system that stores and maintains adaptive local dictionary for each category. The goal of our approach is twofold; to develop a reliable text categorization method on a certain subject domain, and to expand the initial FRT by automatically...

Correspondence analysis and two-way clustering.

Antonio Ciampi, Ana González Marcos, Manuel Castejón Limas (2005)

SORT

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Correspondence analysis followed by clustering of both rows and columns of a data matrix is proposed as an approach to two-way clustering. The novelty of this contribution consists of: i) proposing a simple method for the selecting of the number of axes; ii) visualizing the data matrix as is done in micro-array analysis; iii) enhancing this representation by emphasizing those variables and those individuals which are 'well represented' in the subspace of the chosen axes. The approach...

A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Fokoue, Ernest (2014)

Serdica Journal of Computing

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Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to be analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of...