Huanca Ochoa, Shirley Y.

Publication Search Results

Now showing 1 - 1 of 1

Reducción de la dimensionalidad para optimizar la clasificación de datos funcionales
(2015-05) Huanca Ochoa, Shirley Y.; Acuña Fernández, Edgar; College of Arts and Sciences - Sciences; Santana Morant, Dámaris; Rolke, Wolfgang; Department of Mathematics; Méndez Mella, Héctor
Nowdays throw due to the continuous advance of technology, statisticians have been facing the need to develop new methods to extract meaningful information quickly and efficiently in large data sets, such as functional data. This type of data corresponds to a random observation over an interval. This data are treated theoretically using the definitions and properties of curves; as well as computationally through data mining techniques treating them as high-dimensional vectors. It is in this sense that the application of some methods of feature selection will be advisable prior to any analysis of such data. In this technique a representation of finite size for each curve is used, thus overcoming the problem of high dimensionality. In this work we compare three feature selection procedures with a commonly used reduction dimensionality method for functional data. Results will be presented using two real datasets. This is done in order to compare the effectiveness to minimize the error rate of misclassification in the datasets. The results obtained in this thesis show that the dimensionality reduction using B-Splines yields a better performance that feature selection.