Implement of paper Learning to Represent Review with Tensor Decomposition for Spam Detection,emnlp,2016
RE(50:50):0.7792207792207793
precision recall f1-score support
0 0.75 0.83 0.79 77
1 0.81 0.73 0.77 77
avg/total 0.78 0.78 0.78 154
RE(ND):0.7123050259965338
precision recall f1-score support
0 0.29 0.83 0.44 77
1 0.96 0.69 0.81 500
avg/total 0.87 0.71 0.76 577
RE+PE(50:50):0.811688311688
precision recall f1-score support
0 0.78 0.87 0.82 77
1 0.85 0.75 0.80 77
avg / total 0.82 0.81 0.81 154
RE+PE(ND):0.738301559792
precision recall f1-score support
0 0.32 0.83 0.46 77
1 0.97 0.72 0.83 500
avg/total 0.88 0.74 0.78 577
RE+PE+BiGram(50:50):0.746753246753
precision recall f1-score support
0 0.72 0.82 0.76 77
1 0.79 0.68 0.73 77
avg/total 0.75 0.75 0.75 154
RE+PE+BiGram(ND):0.769497400347
precision recall f1-score support
0 0.35 0.83 0.49 77
1 0.97 0.76 0.85 500
avg/total 0.88 0.77 0.80 577