First question:
The data obtained in the official kdd has 42 columns, and there are 38 columns except [tcp, http, SF, normal]. [0,tcp,http,SF,215,45076,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0.00 ,0.00,0.00,0.00,1.00,0.00,0.00,0,0,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,normal.
] But the same one, there are only 35 columns in the sample data you provided: [0,215,45076,0,0,0,0,0,1,0,0,0,0,0,0,0,0 ,0,0,1,1,0.00,0.00,0.00,0.00,1.00,0.00,0.00,0,0,0.00,0.00,0.00,0.00,0.00]
Second question:
In the sample data, the label is obtained as the last column of each row of data. All [0], what's the point of training? It may also be the reason why I didn't read the paper, I understand it too well.
First question: The data obtained in the official kdd has 42 columns, and there are 38 columns except [tcp, http, SF, normal]. [0,tcp,http,SF,215,45076,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,0.00 ,0.00,0.00,0.00,1.00,0.00,0.00,0,0,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,normal. ] But the same one, there are only 35 columns in the sample data you provided: [0,215,45076,0,0,0,0,0,1,0,0,0,0,0,0,0,0 ,0,0,1,1,0.00,0.00,0.00,0.00,1.00,0.00,0.00,0,0,0.00,0.00,0.00,0.00,0.00]
Second question: In the sample data, the label is obtained as the last column of each row of data. All [0], what's the point of training? It may also be the reason why I didn't read the paper, I understand it too well.