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Mostrando ítems 11-20 de 28
Capítulo de Libro
Efficient Incremental-Ranked Feature Selection in Massive Data
(Chapman and Hall/CRC, 2007)
Capítulo de Libro
Statistical Test-Based Evolutionary Segmentation of Yeast Genome
(2004)
Segmentation algorithms emerge observing fluctuations of DNA sequences in alternative homogeneous domains, which are named segments [1]. The key idea is that two genes that are controlled by a single regulatory system ...
Capítulo de Libro
LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series
(2008)
A new approach is presented in this work with the aim of predicting time series behaviors. A previous labeling of the samples is obtained utilizing clustering techniques and the forecasting is applied using the information ...
Capítulo de Libro
Data streams classification by incremental rule learning with parameterized generalization
(2006)
Mining data streams is a challenging task that requires online systems based on incremental learning approaches. This paper describes a classification system based on decision rules that may store up--to--date border ...
Capítulo de Libro
Fast Feature Selection by Means of Projections
(2003)
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simpler and easy to understand. The algorithm ...
Capítulo de Libro
Multidimensional Data Visual Exploration by Interactive Information Segments
(2004)
Visualization techniques provide an outstanding role in KDD process for data analysis and mining. However, one image does not always convey successfully the inherent information from high dimensionality, very large databases. ...
Capítulo de Libro
Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines
(2007)
Breast cancer is one of the diseases causing the largest number of deaths among women. Its early detection has been proved to be the most effective way to combat it. This work is focused on developing an integral tool able ...
Capítulo de Libro
Discovering decision rules from numerical data streams
(2004)
This paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing data streams. Our approach, named SCALLOP, provides a set of decision rules on demand which ...
Capítulo de Libro
Evolutionary segmentation of yeast genome
(2004)
Segmentation algorithms differ from clustering algorithms with regard to how to deal with the physical location of genes throughout the sequence. Therefore, segments have to keep the original positions of consecutive genes, ...
Capítulo de Libro
Decision Queue Classifier for Supervised Learning Using Rotated Hyperboxes
(1998)
This article describes a new system for learning rules using rotated hyperboxes as individuals of a genetic algorithm (GA). Our method attempts to find out hyperboxes at any orientation by combining deterministic hill-climbing ...