A Novel Neuron in Kernel Domain

Table 3

Evaluation of online learning algorithms with sparsing ability on the large datasets.

Algorithm	Football				Spambase
	Density (%)	Training time (s)	Training mistake (%)	Test mistake (%)	Density (%)	Training time (s)	Training mistake (%)	Test mistake (%)
Perceptron	21.493	6.002	21.493	41.043	25.325	8.179	25.325	40.881
ROMMA	45.605	12.550	20.282	40.905	46.360	15.474	23.403	39.708
ALMA	23.807	6.646	20.430	40.416	28.203	9.440	23.306	39.361
PA	49.531	13.864	20.256	40.694	54.262	17.776	23.757	38.731
DOUL	45.457	19.883	21.775	40.041	49.744	27.720	23.422	39.382
AKNNμ	6.626	0.699	5.631	17.840	23.627	4.619	23.174	17.648
Algorithm	MITFace				Mushrooms
	Density (%)	Training time (s)	Training mistake (%)	Test mistake (%)	Density (%)	Training time (s)	Training mistake (%)	Test mistake (%)
Perceptron	20.764	15.333	20.764	50.366	41.085	40.077	41.085	47.587
ROMMA	32.428	24.932	19.347	50.724	61.679	60.266	41.437	49.569
ALMA	21.138	15.822	18.888	50.365	43.330	42.153	40.501	45.335
PA	43.635	32.526	19.828	48.674	62.218	61.115	41.234	47.378
DOUL	39.419	49.529	19.279	50.193	63.467	192.678	41.075	47.082
AKNNμ	37.366	9.903	7.420	16.038	0.480	0.442	9.992	39.931

∗Bold number shows the algorithm with best efficiency measurement in each dataset.