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Displaying similar documents to “PC-PARIS - An Interactive Software System for Statistical Pattern Recognition”

Smoothing the Catalan tourism micro-data time series.

Manuel Artís Ortuño, Josep Lluís Carrion i Silvestre, Alex Costa Sáenz de San Pedro, Jordi Suriñach Caralt (2002)

Qüestiió

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In this paper we propose a method for smoothing the Catalan tourism time series between 1997 and 2000. These time series, built upon a micro database drawn from a survey conducted by the Statistical Institute of Catalonia, are somewhat volatile due, it would seem, to the incomplete nature of the information. The application of a smoothing procedure based on the combination of classical techniques and weighted moving averages allows us to overcome the problems caused by this lack of information...

Correlation-based feature selection strategy in classification problems

Krzysztof Michalak, Halina Kwaśnicka (2006)

International Journal of Applied Mathematics and Computer Science

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In classification problems, the issue of high dimensionality, of data is often considered important. To lower data dimensionality, feature selection methods are often employed. To select a set of features that will span a representation space that is as good as possible for the classification task, one must take into consideration possible interdependencies between the features. As a trade-off between the complexity of the selection process and the quality of the selected feature set,...

Data mining techniques using decision tree model in materialised projection and selection view.

Y. W. Teh (2004)

Mathware and Soft Computing

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With the availability of very large data storage today, redundant data structures are no longer a big issue. However, an intelligent way of managing materialised projection and selection views that can lead to fast access of data is the central issue dealt with in this paper. A set of implementation steps for the data warehouse administrators or decision makers to improve the response time of queries is also defined. The study concludes that both attributes and tuples, are important...

Reasoning with External Data

Vladan Devedžić, Dušan Velašević, Zoran Božović (1993)

The Yugoslav Journal of Operations Research

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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...

Analysis of correlation based dimension reduction methods

Yong Joon Shin, Cheong Hee Park (2011)

International Journal of Applied Mathematics and Computer Science

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Dimension reduction is an important topic in data mining and machine learning. Especially dimension reduction combined with feature fusion is an effective preprocessing step when the data are described by multiple feature sets. Canonical Correlation Analysis (CCA) and Discriminative Canonical Correlation Analysis (DCCA) are feature fusion methods based on correlation. However, they are different in that DCCA is a supervised method utilizing class label information, while CCA is an unsupervised...

Comparison of speaker dependent and speaker independent emotion recognition

Jan Rybka, Artur Janicki (2013)

International Journal of Applied Mathematics and Computer Science

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This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector...

Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system

Alexandra Carpen-Amarie, Alexandru Costan, Jing Cai, Gabriel Antoniu, Luc Bougé (2011)

International Journal of Applied Mathematics and Computer Science

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Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific...