A data preprocessing is a process of cleaning the data, data integration and data transformation. It intends to reduce some noises and inconsistent data. Data preprocessing is the process of keeping the dataset ready for the process. The results of preprocessing step are later used by data mining algorithms. This paper focus on preprocessing the attributes that are related to crime data and tha...

Hyperspectral Endmember extraction of a set of accurateendmembers is critical for the proper unmixing of Hyperspectral image. Several preprocessing algorithms such as spatial preprocessing (SPP), region based spatial preprocessing (RBSPP), and spatial spectral preprocessing (SSPP) have been developed for the extraction of endmembers. These algorithms require complex operations and huge computat...

One of the reasons ICA (Independent Component Analysis) became so popular is that ICA is a promising tools for a lot of applications. One of the attractive applications is the biological data analysis. There are a lot of works on neurobiological data analysis such as EEG (Electroencephalography), fMRI (functional Magnetic Resonance Imaging), and MEG (Magnetoencephalography), and they show inter...

Preprocessing, a major component of Character Recognition System, has direct effect on the recognition system by its performance. Using wavelet transform, this paper mainly focuses on noise filtering and Edge Detection in a Preprocessing method for NaXi Pictographs Character Recognition. Image denoising is an important issue in image preprocessing. Based on the analysis of thresholding function...

There are real-world dataset where we can found classes with a very different percentage of patterns between them, that is to say we have classes represented by many examples (high percentage of patterns) and classes represented by few examples (low percentage of patterns). These kind of datasets receive the name of “imbalanced datasets”. In the field of classification problems the imbalanced d...

We present a major revamp of the point-location data structure for general two-dimensional subdivisions via randomized incremental construction, implemented in Cgal, the Computational Geometry Algorithms Library. We can now guarantee that the constructed directed acyclic graph G is of linear size and provides logarithmic query time. Via the construction of the Voronoi diagram for a given point ...