MODELS PERFORMANCE

additivemanufacturing - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.87	2.46	0.78	0.82
std	0.03	0.42	0.07	0.07
min	0.82	1.68	0.69	0.69
25%	0.86	2.22	0.72	0.79
50%	0.88	2.49	0.79	0.85
75%	0.89	2.76	0.84	0.87
max	0.89	3	0.88	0.89

additivemanufacturing - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.9	0.3	0.89	0.79
std	0.02	0.05	0.04	0.05
min	0.87	0.21	0.82	0.72
25%	0.89	0.26	0.87	0.75
50%	0.9	0.31	0.89	0.79
75%	0.91	0.34	0.92	0.81
max	0.93	0.37	0.95	0.88

blockchain - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.9	1.11	0.84	0.89
std	0.03	0.51	0.05	0.06
min	0.85	0.34	0.76	0.8
25%	0.89	0.79	0.82	0.85
50%	0.91	1.12	0.83	0.88
75%	0.92	1.39	0.87	0.94
max	0.94	2.11	0.9	0.95

blockchain - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.91	0.22	0.91	0.82
std	0.01	0.04	0.03	0.04
min	0.89	0.18	0.87	0.77
25%	0.9	0.19	0.89	0.78
50%	0.91	0.2	0.9	0.81
75%	0.91	0.23	0.94	0.85
max	0.94	0.32	0.96	0.89

computervision - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.9	1.66	0.86	0.86
std	0.03	0.76	0.06	0.04
min	0.83	0.81	0.77	0.75
25%	0.89	1.14	0.82	0.85
50%	0.91	1.4	0.86	0.87
75%	0.92	2.08	0.91	0.89
max	0.94	3.01	0.95	0.9

computervision - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.9	0.27	0.9	0.82
std	0.02	0.06	0.04	0.04
min	0.87	0.17	0.85	0.75
25%	0.89	0.23	0.87	0.8
50%	0.91	0.26	0.89	0.81
75%	0.92	0.3	0.92	0.85
max	0.93	0.39	0.96	0.89

genomeediting - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.91	1.21	0.85	0.91
std	0.02	0.55	0.04	0.03
min	0.87	0.81	0.8	0.86
25%	0.9	0.94	0.81	0.9
50%	0.91	1.03	0.87	0.91
75%	0.93	1.11	0.88	0.94
max	0.94	2.66	0.88	0.96

genomeediting - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.92	0.23	0.89	0.87
std	0.02	0.04	0.03	0.04
min	0.89	0.15	0.84	0.82
25%	0.9	0.21	0.87	0.85
50%	0.92	0.23	0.89	0.87
75%	0.93	0.25	0.91	0.89
max	0.95	0.3	0.94	0.95

hydrogenstorage - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.87	2.43	0.78	0.84
std	0.04	0.8	0.05	0.07
min	0.81	0.99	0.71	0.72
25%	0.84	2.1	0.75	0.8
50%	0.87	2.41	0.76	0.83
75%	0.88	2.72	0.82	0.89
max	0.94	4.08	0.86	0.94

hydrogenstorage - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.87	0.35	0.85	0.72
std	0.02	0.04	0.04	0.05
min	0.84	0.25	0.76	0.62
25%	0.86	0.34	0.84	0.71
50%	0.86	0.35	0.86	0.73
75%	0.88	0.37	0.88	0.75
max	0.9	0.42	0.9	0.79

naturallanguageprocessing - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.89	0.97	0.81	0.88
std	0.03	0.2	0.06	0.05
min	0.82	0.62	0.72	0.8
25%	0.88	0.87	0.76	0.86
50%	0.88	0.96	0.83	0.88
75%	0.91	1.14	0.85	0.9
max	0.94	1.23	0.87	0.98

naturallanguageprocessing - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.9	0.27	0.89	0.79
std	0.02	0.06	0.03	0.05
min	0.87	0.14	0.84	0.74
25%	0.88	0.24	0.87	0.77
50%	0.89	0.27	0.88	0.78
75%	0.91	0.3	0.91	0.81
max	0.95	0.36	0.95	0.9

selfdrivingvehicle - cnn

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.8	3.6	0.69	0.71
std	0.04	0.74	0.06	0.09
min	0.72	2.57	0.55	0.54
25%	0.78	3.07	0.66	0.65
50%	0.8	3.57	0.69	0.73
75%	0.82	4.02	0.72	0.77
max	0.85	4.85	0.78	0.83

selfdrivingvehicle - mlp

	binary_accuracy	loss	precision	recall
count	10	10	10	10
mean	0.82	0.51	0.8	0.63
std	0.02	0.06	0.06	0.04
min	0.77	0.43	0.71	0.57
25%	0.82	0.47	0.77	0.6
50%	0.82	0.5	0.79	0.65
75%	0.84	0.54	0.82	0.66
max	0.85	0.63	0.94	0.68