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The Efficient Market Hypothesis states that the value of an asset is given by all information available in the present moment. However, there is no possibility that a single financial analyst be aware of all published news which refers to a collection of stocks in the moment they are published. Thus, a computer system that applies text mining techniques and the GARCH model for predicting the volatility...
Dimensionality reduction applied to gene expression is challenging for machine learning algorithms due to a small number of samples and a high number of attributes. This paper proposes a preprocessing phase by means of random projection method in microarray data. Experimental results are promising and it shows that the use of this method improves the performance of classification algorithms.
The main objective of this work is to present an exploratory approach on electroencephalographic (EEG) signal, analyzing the patterns on the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for data mining on EEG signal based on continuous wavelet...
Many results in the literature indicate that the incremental approach to association mining leads to gain regarding the time needed to obtain the rules, but there is no evaluation about their quality, compared to non-incremental algorithms. This paper presents the comparison of usage of two typical algorithms representing each approach: APriori and ZigZag. Execution time clearly shows the advantage...
Data clustering methods have become standard techniques in the analysis of gene expression data. They are used in a variety of tasks ranging from simple data pre- treatment for posterior analysis to the identification of important information, such as gene function and/or the participation of a group of genes in a given biological process. Data clustering methods also offer advantages to the biologist...
Many times, when studying gene expression data, unknown attributes, which can be redundant and even, in certain cases, irrelevant, are manipulated. The application of selection attributes algorithms as a preprocessing can help in the knowledge discovery database process. This paper is about applying selection attributes algorithms in two gene expression databases. The result shows that the use of...
For data miners, bioinformatics pose a most demanding challenge than only creating efficient algorithms. They should work with databases that are more "horizontal" than "vertical", as the data consist of a few samples of a large (sometimes huge) number of attributes in the case of micro-arrays. More important is the fact that there is a priori biological knowledge saying that only...
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