Fast Density Clustering Algorithm for Numerical Data and Categorical Data

Table 5

Twelve data sets from UCI.

Data sets	Attributes				Number of instances
Aggregation	2	2	0	7	788
Spiral	2	2	0	3	312
Jain	2	2	0	2	373
Flame	2	2	0	2	240
Iris	4	4	0	3	150
Breast	9	9	0	2	699
Soybean	35	0	35	4	47
Zoo	15	1	14	7	101
Acute	7	1	6	2	120
Statlog (Heart)	13	5	8	2	270
Credit	15	9	6	2	690
KDD CUP-99	41	34	7		1000

is the number of numerical attributes, is the number of categorical attributes, “” is for unknown parameters, and is the number of clusters.