A New Symbolic Dissimilarity Measure for Multivalued Data Type and Novel Dissimilarity Approximation Techniques
نویسندگان
چکیده
منابع مشابه
A New Symbolic Dissimilarity Measure for Multivalued Data Type and Novel Dissimilarity Approximation Techniques
In this paper a new statistical measure for estimating the degree of dissimilarity between two symbolic objects whose features are multivalued symbolic data type is proposed. In addition two new simple representation techniques viz., interval type and magnitude type for the computed dissimilarity between the symbolic objects are introduced. The dissimilarity matrices obtained are not necessaril...
متن کاملComparing Dissimilarity Measures for Symbolic Data Analysis
Nowadays, data analysts are confronted with new challenges: they are asked to process data that go beyond the classical framework, as in the case of data concerning more or less homogeneous classes or groups of individuals (second-order objects) instead of single individuals (first-order objects). A typical situation is that of census data, which raise privacy issues in all governmental agencie...
متن کاملA New Dissimilarity Measure between Feature-Vectors
Distance measures is very important in some clustering and machine learning techniques. At present there are many such measures for determining the dissimilarity between the featurevectors, but it is very important to make a choice that depends on the problem to be solved. This paper proposes a simple but robust distance measure called Reference Distance Weighted, for calculating distance betwe...
متن کاملA New Dissimilarity Measure for Clustering Seismic Signals
Hypocenter and focal mechanism of an earthquake can be determined by the analysis of signals, named waveforms, related to the wave field produced and recorded by a seismic network. Assuming that waveform similarity implies the similarity of focal parameters, the analysis of those signals characterized by very similar shapes can be used to give important details about the physical phenomena whic...
متن کاملComparing dissimilarity measures for probabilistic symbolic objects
Symbolic data analysis generalizes some standard statistical data mining methods, such as those developed for classification and clustering tasks, to the case of symbolic objects (SOs). These objects, informally defined as “aggregated data” because they synthesize information concerning a group of individuals of a population, ensure confidentiality of original data, nevertheless they pose new p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2010
ISSN: 0975-8887
DOI: 10.5120/482-792