Create baseline based on `An Evaluation and Performance study on BODMAS dataset for Malware Analysis`

https://gist.github.com/attilamester/ef6db70ae99267006aec5b269003f832

Baseline classifier:


Training on 129314 samples with min class size 100 | unique classes: 59

model   scaler  n_samples   dt (s)  f1_micro    f1_macro    acc bacc    prec_micro  prec_macro  rec_micro   rec_macro   f1_micro    f1_macro
0   LogisticRegression  StandardScaler  None    312.1   0.9320  0.5790  0.9320  0.5988  0.9320  0.6048  0.9320  0.5878  0.9320  0.5790
1   KNeighborsClassifier    StandardScaler  None    3.1 0.9401  0.5389  0.9401  0.5580  0.9401  0.5671  0.9401  0.5477  0.9401  0.5389
2   DecisionTreeClassifier  StandardScaler  None    1023.6  0.9328  0.5294  0.9328  0.5969  0.9328  0.5312  0.9328  0.5567  0.9328  0.5294
3   RandomForestClassifier  StandardScaler  None    666.8   0.9517  0.6264  0.9517  0.6182  0.9517  0.6743  0.9517  0.6124  0.9517  0.6264
4   LogisticRegression  StandardScaler  None    108.7   0.9459  0.8596  0.9459  0.8586  0.9459  0.8701  0.9459  0.8586  0.9459  0.8596
5   KNeighborsClassifier    StandardScaler  None    3.0 0.9560  0.8629  0.9560  0.8652  0.9560  0.8683  0.9560  0.8652  0.9560  0.8629
6   DecisionTreeClassifier  StandardScaler  None    329.6   0.9526  0.8661  0.9526  0.8735  0.9526  0.8600  0.9526  0.8735  0.9526  0.8661
7   RandomForestClassifier  StandardScaler  None    199.5   0.9656  0.8887  0.9656  0.8809  0.9656  0.9078  0.9656  0.8809  0.9656

attilamester / malflow

Create baseline based on `An Evaluation and Performance study on BODMAS dataset for Malware Analysis` #152