Automation has arrived to Parallel Coordinates. A geometrically motivated classifier is presented and applied, with both training and testing stages, to 3 real datasets. Our results compared to those from 23 other classifiers have the least error. The algorithm is based on parallel coordinates and : has very low computational complexity in the number of variables and the size of the dataset – c...

Identifying the projective group for patterns by developing the camera model, the projective Fourier transform and its inverse are obtained in analogy with the classical, that is, Euclidean Fourier analysis. Projectively adapted properties are demonstrated in a numerical test. Using the expression of the projective Fourier integral by a standard Fourier integral in the coordinates given by the ...

This paper proposes an asymmetric-volatility based method for cluster analysis of stock returns. Using the information about the estimated parameters in the TARCH equation, we compute a distance matrix for the stock returns. Clusters are formed by looking to the hierarchical structure tree (or dendrogram) and the computed principal coordinates. We employ these techniques to investigate the simi...

Recently manifold learning has attracted extensive interest in machine learning and related communities. This paper investigates the noise manifold learning problem, which is a key issue in applying manifold learning algorithm to practical problems. We propose a robust version of LTSA algorithm called RLTSA. The proposed RLTSA algorithm makes LTSA more robust from three aspects: firstly robust ...

Principal components analysis (PCA) is a classical method for the reduction of dimensionality of data in the form of n observations (or cases) of a vector with p variables. Contemporary data sets often have p comparable to, or even much larger than n. Our main assertions, in such settings, are (a) that some initial reduction in dimensionality is desirable before applying any PCA-type search for...

a procedure for an efficient recovering of reflectance spectra of acrylic paint samples from cie tristimulus color values is described. by fixing a certain criteria based on color difference value, the proposed technique preliminarily selects a series of suitable samples from a main dataset containing the reflectance values of a series of different acrylic paint samples, based on the color spec...

medicinal plant species constitute a considerable part of the flora in iran and play a major role in the composition of plant communities. therefore, it is necessary to recognize the factors leading to the establishment and distribution of vegetation. for data sampling (2012), land units were specified. the plot size was determined using minimal area method and number of plots was determined by...

Tristimulus values (X, Y, Z) and CIELAB colourimetric coordinates have been measured in m. Longissimus dorsi and m. Triceps braquialis caput longum muscles in 86 light carcasses of lambs from different origins. By applying to these data different mathematical methods (ANOVA, Discriminant Analysis, Principal Components Analysis and Cluster Analysis) we have obtained a good classification of thes...