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Efecto de casos anómalos en máquinas de vectores de soporte
(2009-03)
Support Vector Machines (SVM) is a new technique of classification that has received much attention in recent years. In many applications, the SVM has shown better performance than machine learning methods, and it has been ...
Análisis sobre métodos de pruebas de hipótesis múltiple en la identificación de genes diferencialmente expresados
(2009-07)
The Human Genome Project is the most important reason for the surge of new technologies in the microarray area. These technologies facilitate the experimentation with a large number of genes simultaneously. These experiments ...
Contributions to parallel and distributed computing in knowledge discovery and data mining
(2006)
Recently databases are increasing continuously without bound, due to new data acquisition technologies. One challenge is how to gain knowledge from these large data sets. In this thesis, we analyze and improve the algorithmic ...
On applications of rough sets theory to knowledge discovery
(2007)
Knowledge Discovery in Databases (KDD) is the nontrivial extraction of implicit, previously unknown and potentially useful information from data. Data preprocessing is a step of the KDD process that reduces the complexity ...
Generalizaciones de minimos cuadrados parciales con aplicación en clasificacion supervisada
(2004)
The development of technologies such as microarrays has generated a large amount of data. The main characteristic of this kind of data it is the large number of predictors (genes) and few observations (experiments). Thus, ...
Métodos para mejorar la calidad de un conjunto de datos para descubrir conocimiento
(2007)
Today, data generation is growing exponentially in both directions; instances (rows) and features (columns). This causes that many datasets can not be analyzed without preprocessing. The large size of the dataset to be ...
A comparison in cluster validation techniques
(2004)
Clustering may be defined as a process that aims to find partitions of similar objects. It is an unsupervised recognition procedure since there are no predefined classes that indicate grouping properties in the data set. ...
A computational environment for data preprocessing in supervised classification
(2004)
In this thesis, a data preprocessing environment has been created, for use in a supervised classification context, with the Windows platform of the R programming language and environment for statistical computing and ...
Clasificación noparamétrica en datos direccionales
(2004)
In a supervised classification problem, when the vectors of data are direction- al, it means, that they take values on a k-dimensional sphere, the application of the algorithms of pattern recognition as k-nearest-neighbour ...
Algorithms for non-parametric classifiers in multi-relational data mining
(2006)
Over the last decades, due to the advances in information technologies, both the industrial and scientific communities have acquired large volumes of data in digital form. Most of these data sets are stored using relational ...