… Our results indicate that our Categorical Data Map offers an effective analysis method for …
We conclude that the Categorical Data Map effectively analyzes large categorical datasets, …

… In this section, we discuss how to map a multidimensional data pattern to a set of distance
hierarchies. Let , … a categorical value or … of a GSOM unit toward its correspondent attribute …

… categorical data analysis. We show how these statistics can be used as a way to map
categorical data to continuous space given a labeled reference … This paper is an attempt towards …

… map categorical values to vectors using some embedding technique, we first need to map the
categorical … We conjecture that mapping categorical values to integers using some hashing …

… Similar to Radviz, the location of a projected point indicates how much it gravitates towards
… cars map to a long cluster centered between Weight and Horsepower and reaching towards …

… states) are transported via statistical maps (equivalently, fuzzy random variables, operational
random variables, Markov kernels, observables). We deal with categorical aspects of the …

… , so that the color mapping matches typical colors for items defining the categorical data. Lin
et al. [… He is currently working towards a master degree in Shenzhen University. His research …

… , the adaptation is realized by moving their corresponding points in the hierarchies toward
the mapping points of the input, as indicated by the arrows in Fig. 1 where M moves toward X. …

… characteristics of datasets with categorical data and respecting semantic information as well.
… After a short recapitulation of the cartographic constraints applicable to categorical data and …

… that maps categorical data into a numerical data space via a … the generated image data set
as well as to visualize the data. … conditions under which the data mapping is efficient and yet …