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Table 12 Formal description of the data set

From: PUMD: a PU learning-based malicious domain detection framework

Method

Labeled sample

Unlabeled sample

TrainSet

TestSet

Mali DN

Benign DN

P

N

PUMD

\(P = c *Mali\)

–

\(U = D - P\)

W(P)

\(\cup w(U)\)

U

PU_biased

W(U)

PU_empirical

\(W(P) \cup W(U)\)

mix_supervised*

 

\(N_{mix} = Sample_{size(P)}(D-P)\)

\(D - P - N_{mix}\)

P

\(N_{mix}\)

pure_supervised

 

\(N_{pure} = Sample_{size(P)}(Benign)\)

\(D - P - N_{pure}\)

\(N_{pure}\)

unsupervised

–

–

D

D

  1. *baseline