Resultados Spam Filter - ERBD (Abril/2025)

	A	B	C	D	E	F	I	J	K	L	M	N
1	Logistic Regression						Näive Bayes
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3		300 SPAM	spam_ham_dataset.csv			735 HAM		300 SPAM	spam_ham_dataset.csv			735 HAM
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5			precision	recall	f1-score	support			precision	recall	f1-score	support
6		ham	1.00	0.95	0.97	735		ham	0.95	1.00	0.97	735
7		spam	0.88	1.00	0.94	300		spam	0.99	0.87	0.93	300
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9		accuracy			0.96	1035		accuracy			0.96	1035
10		macro avg	0.94	0.97	0.95	1035		macro avg	0.97	0.93	0.95	1035
11		weighted avg	0.97	0.96	0.96	1035		weighted avg	0.96	0.96	0.96	1035
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14				Pred HAM	PRED SPAM					Pred HAM	PRED SPAM
15			Real HAM	695	40				Real HAM	732	3
16			Real SPAM	0	300				Real SPAM	38	262
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20		149 SPAM	spam.csv			966 HAM		149 SPAM	spam.csv			966 HAM
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22			precision	recall	f1-score	support			precision	recall	f1-score	support
23		ham	0.99	0.99	0.99	966		ham	0.97	1.00	0.99	966
24		spam	0.94	0.91	0.93	149		spam	0.99	0.81	0.89	149
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26		accuracy			0.98	1115		accuracy			0.97	1115
27		macro avg	0.97	0.95	0.6	1115		macro avg	0.98	0.91	0.94	1115
28		weighted avg	0.98	0.98	0.98	1115		weighted avg	0.97	0.97	0.97	1115
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31				Pred HAM	PRED SPAM					Pred HAM	PRED SPAM
32			Real HAM	958	8				Real HAM	965	1
33			Real SPAM	13	136				Real SPAM	28	121
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