A Method for Reducing Visual Clutter in Parallel Coordinates Visualization Based on Dimension Reordering
A parallel coordinate and reordering technology, applied in the field of information visualization, can solve the problems of ignoring visual clutter and not fully reflecting visual clutter, and achieve the effect of reducing visual clutter and efficient approximate calculation methods.
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[0039] Specific embodiments of the present invention are further described below.
[0040] Step 1: Input data set D={d 1 , d 2 ,...,d m}, where m is the sample size, d i =(d i,1 , d i,2 ,...,d i,n ), 1≤i≤m, n is the attribute dimension, and the attribute set is A={A 1 ,A 2 ,...,A n}; if A contains category attributes, record it as A class ={C 1 ,C 2 ,...,C l}, class is the dimension where the category attribute is located; if A does not contain the category attribute, use the clustering method to obtain the sample category attribute and record it as A class ; The sample sets of each category are denoted as l is the number of categories;
[0041] Step 2: Calculate the clutter of the sample between any two attributes Clutter(A p ,A q ), 1≤p, q≤n, to obtain the clutter matrix Clutter, the specific steps are as follows:
[0042] Step 2.1: Calculate according to the intersection of the representative curves of different categories of samples, the specific steps ...
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