Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis

Table 9

Training (a), validation (b), and test (c) accuracies of tree-based classifiers for various pretrained networks.

(a) Training accuracy of tree-based classifiers for various pretrained networks

Classifier	Training accuracy (%)
	AlexNet	DenseNet-201	GoogleNet	ResNet-50	VGG16	VGG19
BF tree	99.20	98.76	98.41	98.41	98.45	98.13
CS forest	99.01	99.52	99.44	99.28	99.52	99.88
Decision stump	32.14	33.09	31.42	31.98	29.84	32.65
Extra tree	100.00	100.00	100.00	100.00	100.00	100.00
Forest PA	99.72	99.88	99.84	99.84	99.48	99.68
FT	99.92	99.96	99.76	99.88	99.48	99.92
Hoeffding tree	93.05	80.91	31.90	90.59	72.06	51.38
J48	99.28	99.20	98.96	99.00	98.92	99.08
J48graft	99.28	99.20	98.96	99.00	98.92	99.08
LAD tree	89.16	91.50	86.74	89.40	86.26	89.60
LMT	99.56	100.00	99.96	99.80	99.92	99.72
NB tree	99.88	100.00	99.96	100.00	99.84	99.96
Optimized forest	100.00	100.00	100.00	100.00	100.00	100.00
Random forest	100.00	100.00	100.00	100.00	100.00	100.00
Random tree	100.00	100.00	100.00	100.00	100.00	100.00
REP tree	95.59	97.14	95.11	95.83	95.19	96.82
Simple cart	99.24	98.92	98.05	98.25	98.45	98.92

(b) Validation accuracy of tree-based classifiers for various pretrained networks

Classifier	Validation accuracy (%)
	AlexNet	DenseNet-201	GoogleNet	ResNet-50	VGG16	VGG19
BF tree	93.88	94.84	93.21	93.88	93.13	94.08
CS forest	95.79	97.30	95.63	95.55	96.03	96.66
Decision stump	32.10	33.05	31.42	31.78	30.07	32.53
Extra tree	91.78	91.58	91.54	91.70	91.15	91.34
Forest PA	97.93	98.69	97.26	98.49	97.69	97.38
FT	98.37	99.13	97.73	98.57	97.42	98.38
Hoeffding tree	92.50	91.11	88.49	90.03	83.92	89.84
J48	94.44	95.39	93.61	93.84	94.20	94.20
J48graft	94.24	94.23	93.84	93.73	93.92	96.65
LAD tree	88.01	89.48	87.06	87.34	83.76	87.97
LMT	98.69	99.48	97.93	98.69	97.50	98.37
NB tree	93.01	93.49	94.66	92.38	88.41	89.88
Optimized forest	99.16	99.64	98.69	99.32	98.69	99.96
Random forest	99.08	99.68	98.76	99.36	98.73	99.28
Random tree	93.01	94.84	93.25	98.05	93.21	92.81
REP tree	92.81	93.45	91.82	91.36	91.86	91.78
Simple cart	94.28	95.31	93.45	93.69	93.25	94.44

(c) Test accuracy of tree-based classifiers for various pretrained networks

Classifier	Test accuracy (%)
	AlexNet	DenseNet-201	GoogleNet	ResNet-50	VGG16	VGG19
BF tree	95.55	95.23	93.33	93.96	94.12	93.17
CS forest	96.66	97.77	96.19	95.39	96.19	97.62
Decision stump	32.69	33.17	37.52	31.90	29.36	32.69
Extra tree	93.17	91.74	90.85	91.26	92.69	92.53
Forest PA	98.09	98.57	97.71	98.73	97.69	97.93
FT	98.41	99.2	97.90	99.04	97.3	98.41
Hoeffding tree	93.01	80.31	19.42	89.84	70.79	49.68
J48	95.23	95.07	94.66	94.13	94.76	94.44
J48graft	95.71	95.23	95.80	93.96	93.96	94.28
LAD tree	89.52	90.15	84.57	86.98	83.33	86.82
LMT	99.20	99.74	98.28	99.36	98.25	98.41
NB tree	94.44	95.55	95.42	96.19	93.17	93.33
Optimized forest	99.04	99.80	99.03	99.68	99.36	99.80
Random forest	99.52	99.84	99.23	99.68	99.68	99.84
Random tree	94.44	94.12	90.47	90.31	93.53	94.60
REP tree	92.69	95.39	90.85	91.74	92.16	93.49
Simple cart	95.55	95.07	93.33	94.12	94.28	94.12

Boldface entries represent the highest values obtained.