F1_MEAN_ACC_X <= 0.0108261
|   F3_MEAN_ACC_Z <= -0.123901: fanmian (50.0)
|   F3_MEAN_ACC_Z > -0.123901: jingzhi (25.0)
F1_MEAN_ACC_X > 0.0108261
|   F3_MEAN_ACC_Z <= 0.00497055: daoli (57.0)
|   F3_MEAN_ACC_Z > 0.00497055: touzhi (25.0)

Number of Leaves: 4
Size of the tree: 7

Classes:
=> daoli, fanmian, jingzhi, touzhi

Features:
=> F1_MEAN_ACC_X, F2_MEAN_ACC_Y, F3_MEAN_ACC_Z, F4_MEAN_ACC_V2, F5_VARIANCE_ACC_V2, F6_VARIANCE_GYR_V2, F7_ENERGY_GYR_X, F8_ENERGY_GYR_Y, F9_ENERGY_GYR_Z, F10_ENERGY_GYR_V2, F11_PEAK_TO_PEAK_ACC_V2, F12_PEAK_TO_PEAK_GYR_V2

========================== Cross-Validation: 5 fold/s ==========================

Accuracy iter 1:	100.00 %
Accuracy iter 2:	100.00 %
Accuracy iter 3:	93.75 %
Accuracy iter 4:	97.22 %
Accuracy iter 5:	96.67 %

Average accuracy:	97.53 %
Std dev accuracy:	2.34 %

=============== Whole data training with Confidence Factor: 0.00 ===============

Confusion Matrix:
daoli	fanmian	jingzhi	touzhi	<-- classified as
daoli	57	0	0	0	
fanmian	0	50	0	0	
jingzhi	0	0	25	0	
touzhi	0	0	0	25	

Total Number of Instances:	157
Correctly Classified Instances:	157
Incorrectly Classified Instances:	0

Accuracy:	100.00 % 
Cohen's kappa:	28.39 %

Report:	precision	recall	support
daoli	1.00	1.00	57
fanmian	1.00	1.00	50
jingzhi	1.00	1.00	25
touzhi	1.00	1.00	25

avg/total	1.00	1.00	157