Improvement of K-Means Algorithm and Its Application in Air Passenger Grouping

Table 6

ACC and FMI evaluation results on real-world datasets with AP, MS, DBSCAN.

Dataset	ACC				FMI
	AP	MS	DBSCAN	k-2o	AP	MS	DBSCAN	k-2o
Breast-cancer	0.1353	0.7153	0.6626	0.8910	0.2491	0.7117	0.6775	0.8286
Banknote	0.1013	0.5554	0.5554	0.5954	0.2230	0.7112	0.7112	0.5231
Bupa	0.0841	0.5188	0.9913	0.5768	0.1540	0.6224	0.7073	0.5136
Compound	0.3584	0.7393	0.3960	0.6365	0.4530	0.8159	0.4972	0.6181
Ct	0.2172	0.4977	0.7873	0.8325	0.3267	0.6724	0.6633	0.7199
Hayes-Roth	0.1515	0.3864	0.3561	0.4469	0.1981	0.5876	0.3436	0.3519
Iris	0.4133	0.6667	0.3333	0.8933	0.5145	0.7715	0.5735	0.8208
Libras	0.3889	0.0667	0.1278	0.4416	0.3333	0.2531	0.2429	0.3389
Parkinsons	0.1590	0.6513	0.6154	0.6307	0.2465	0.6857	0.6436	0.5889
Penbased	0.1018	0.1041	0.1195	0.6035	0.2416	0.3164	0.3080	0.5582
Vowel	0.1657	0.0909	0.0909	0.3645	0.2266	0.3000	0.3000	0.2868
Waveform21	0.0368	0.3392	0.3374	0.5018	0.1067	0.5773	0.5613	0.5047
Waveform40	0.0650	0.3384	0.3384	0.5160	0.1124	0.5773	0.5773	0.5035
Wdbc	0.1353	0.7153	0.6626	0.8910	0.2491	0.7117	0.6775	0.8286
Wine	0.3427	0.3989	0.6966	0.7022	0.4604	0.5813	0.6482	0.5809
Number	0	2	1	—	0	9	7	—