runs.txt

 =====> Random Forrest <=====
BAG-OF-WORDS:
              precision    recall  f1-score   support

      Benign     1.0000    0.9331    0.9654       359
   Malicious     0.9420    1.0000    0.9701       390

    accuracy                         0.9680       749
   macro avg     0.9710    0.9666    0.9678       749
weighted avg     0.9698    0.9680    0.9679       749

Average Accuracy: 484.0
Best: 100.0
Worst: 92.0

Average F1: 297.8494623655914
Best: 100.0
Worst: 0.0

Average Precision: 295.7894736842105
Best: 100.0
Worst: 0.0
True Positive: 390 True Negative: 335 False positive: 24 False negative: 0

TF-IDF:
              precision    recall  f1-score   support

      Benign     1.0000    0.9304    0.9639       359
   Malicious     0.9398    1.0000    0.9689       390

    accuracy                         0.9666       749
   macro avg     0.9699    0.9652    0.9664       749
weighted avg     0.9686    0.9666    0.9665       749

Average Accuracy: 483.33333333333337
Best: 100.0
Worst: 92.0

Average F1: 297.8494623655914
Best: 100.0
Worst: 0.0

Average Precision: 295.7894736842105
Best: 100.0
Worst: 0.0
True Positive: 390 True Negative: 334 False positive: 25 False negative: 0

Doc2Vec:
              precision    recall  f1-score   support

      Benign     0.7613    0.8886    0.8201       359
   Malicious     0.8788    0.7436    0.8056       390

    accuracy                         0.8131       749
   macro avg     0.8201    0.8161    0.8128       749
weighted avg     0.8225    0.8131    0.8125       749

Average Accuracy: 406.4519015659955
Best: 90.0
Worst: 67.78523489932886

Average F1: 256.3984555984556
Best: 91.42857142857143
Worst: 0.0

Average Precision: 295.23809523809524
Best: 100.0
Worst: 0.0
True Positive: 290 True Negative: 319 False positive: 40 False negative: 100

------------------------------------------------------------------------------------------------------------------------
 =====> ADABOOST <=====
BAG-OF-WORDS:
              precision    recall  f1-score   support

      Benign     0.9579    0.9499    0.9538       359
   Malicious     0.9542    0.9615    0.9579       390

    accuracy                         0.9559       749
   macro avg     0.9560    0.9557    0.9559       749
weighted avg     0.9560    0.9559    0.9559       749

Average Accuracy: 477.9821029082774
Best: 97.31543624161074
Worst: 94.0

Average F1: 292.45015850560367
Best: 98.63945578231292
Worst: 0.0

Average Precision: 297.7011494252873
Best: 100.0
Worst: 0.0
True Positive: 375 True Negative: 341 False positive: 18 False negative: 15

TF-IDF:
              precision    recall  f1-score   support

      Benign     0.9576    0.9443    0.9509       359
   Malicious     0.9494    0.9615    0.9554       390

    accuracy                         0.9533       749
   macro avg     0.9535    0.9529    0.9532       749
weighted avg     0.9533    0.9533    0.9533       749

Average Accuracy: 476.61297539149894
Best: 98.0
Worst: 91.94630872483222

Average F1: 293.1724731724732
Best: 98.98989898989899
Worst: 0.0

Average Precision: 296.8085106382979
Best: 100.0
Worst: 0.0
True Positive: 375 True Negative: 339 False positive: 20 False negative: 15

Doc2Vec:
               precision    recall  f1-score   support

      Benign     0.8063    0.8579    0.8313       359
   Malicious     0.8610    0.8103    0.8349       390

    accuracy                         0.8331       749
   macro avg     0.8337    0.8341    0.8331       749
weighted avg     0.8348    0.8331    0.8332       749

Average Accuracy: 416.55033557046977
Best: 90.66666666666666
Worst: 74.0

Average F1: 267.63347919563023
Best: 92.13483146067416
Worst: 0.0

Average Precision: 294.2528735632184
Best: 100.0
Worst: 0.0
True Positive: 316 True Negative: 308 False positive: 51 False negative: 74


------------------------------------------------------------------------------------------------------------------------
 =====> SVM <=====
              precision    recall  f1-score   support

      Benign     0.9282    0.8997    0.9137       359
   Malicious     0.9102    0.9359    0.9229       390

    accuracy                         0.9186       749
   macro avg     0.9192    0.9178    0.9183       749
weighted avg     0.9188    0.9186    0.9185       749

Average Accuracy: 459.3109619686801
Best: 96.66666666666667
Worst: 87.33333333333333

Average F1: 288.82924681936015
Best: 98.29351535836179
Worst: 0.0

Average Precision: 295.74468085106383
Best: 100.0
Worst: 0.0
True Positive: 365 True Negative: 323 False positive: 36 False negative: 25

TF-IDF:
             precision    recall  f1-score   support

      Benign     0.9653    0.9304    0.9475       359
   Malicious     0.9380    0.9692    0.9533       390

    accuracy                         0.9506       749
   macro avg     0.9516    0.9498    0.9504       749
weighted avg     0.9511    0.9506    0.9506       749

Average Accuracy: 475.3109619686802
Best: 96.66666666666667
Worst: 92.0

Average F1: 293.23064006862444
Best: 98.29351535836179
Worst: 0.0

Average Precision: 294.79166666666663
Best: 100.0
Worst: 0.0
True Positive: 378 True Negative: 334 False positive: 25 False negative: 12

Doc2Vec:
               precision    recall  f1-score   support

      Benign     0.6364    0.6240    0.6301       359
   Malicious     0.6599    0.6718    0.6658       390

    accuracy                         0.6489       749
   macro avg     0.6482    0.6479    0.6480       749
weighted avg     0.6486    0.6489    0.6487       749

Average Accuracy: 324.44742729306483
Best: 80.0
Worst: 55.333333333333336

Average F1: 235.60847352518468
Best: 84.04255319148936
Worst: 0.0

Average Precision: 281.44329896907215
Best: 100.0
Worst: 0.0
True Positive: 262 True Negative: 224 False positive: 135 False negative: 128

------------------------------------------------------------------------------------------------------------------------
 =====> KNN <=====
 Bag-of-Words
               precision    recall  f1-score   support

      Benign     0.9570    0.4958    0.6532       359
   Malicious     0.6785    0.9795    0.8017       390

    accuracy                         0.7477       749
   macro avg     0.8177    0.7377    0.7274       749
weighted avg     0.8120    0.7477    0.7305       749

Average Accuracy: 373.9865771812081
Best: 97.98657718120806
Worst: 15.333333333333332

Average F1: 278.5381355932203
Best: 98.98305084745762
Worst: 0.0

Average Precision: 268.42105263157896
Best: 100.0
Worst: 0.0
True Positive: 382 True Negative: 178 False positive: 181 False negative: 8

 TF-IDF
               precision    recall  f1-score   support

      Benign     0.9514    0.9276    0.9394       359
   Malicious     0.9348    0.9564    0.9455       390

    accuracy                         0.9426       749
   macro avg     0.9431    0.9420    0.9424       749
weighted avg     0.9428    0.9426    0.9426       749

Average Accuracy: 471.29753914988817
Best: 96.0
Worst: 92.66666666666666

Average F1: 291.27584683133466
Best: 97.26027397260273
Worst: 0.0

Average Precision: 294.7368421052631
Best: 100.0
Worst: 0.0
True Positive: 373 True Negative: 333 False positive: 26 False negative: 17

Doc2Vec
              precision    recall  f1-score   support

      Benign     0.8941    0.7068    0.7895      2149
   Malicious     0.7751    0.9234    0.8428      2351

    accuracy                         0.8200      4500
   macro avg     0.8346    0.8151    0.8161      4500
weighted avg     0.8319    0.8200    0.8173      4500

Average Accuracy: 82.0
Best: 86.66666666666667
Worst: 75.33333333333333

Average F1: 84.2448628628399
Best: 89.13043478260869
Worst: 77.84431137724552

Average Precision: 77.58394533696821
Best: 85.41666666666666
Worst: 68.62745098039215
True Positive: 2171 True Negative: 1519 False positive: 630 False negative: 180
------------------------------------------------------------------------------------------------------------------------
=====> Decision Tree <=====
Bag-of-Words
             precision    recall  f1-score   support

      Benign     0.9713    0.9578    0.9645      2157
   Malicious     0.9617    0.9740    0.9678      2343

    accuracy                         0.9662      4500
   macro avg     0.9665    0.9659    0.9661      4500
weighted avg     0.9663    0.9662    0.9662      4500

Average Accuracy: 96.62222222222222
Best: 98.66666666666667
Worst: 92.66666666666666

Average F1: 96.77036034537925
Best: 98.87640449438202
Worst: 92.81045751633987

Average Precision: 96.20556274981672
Best: 100.0
Worst: 92.20779220779221
True Positive: 2282 True Negative: 2066 False positive: 91 False negative: 61

TF-IDF
              precision    recall  f1-score   support

      Benign     0.9722    0.9589    0.9655      2192
   Malicious     0.9615    0.9740    0.9677      2308

    accuracy                         0.9667      4500
   macro avg     0.9669    0.9665    0.9666      4500
weighted avg     0.9667    0.9667    0.9667      4500

Average Accuracy: 96.66666666666669
Best: 99.33333333333333
Worst: 93.33333333333333

Average F1: 96.768228096684
Best: 99.40119760479043
Worst: 94.03973509933775

Average Precision: 96.16146891696812
Best: 100.0
Worst: 92.20779220779221
True Positive: 2248 True Negative: 2102 False positive: 90 False negative: 60

Doc2Vec
              precision    recall  f1-score   support

      Benign     0.8273    0.7960    0.8114      2167
   Malicious     0.8170    0.8457    0.8311      2333

    accuracy                         0.8218      4500
   macro avg     0.8222    0.8209    0.8212      4500
weighted avg     0.8220    0.8218    0.8216      4500

Average Accuracy: 82.17777777777776
Best: 89.33333333333333
Worst: 75.33333333333333

Average F1: 83.06593716617073
Best: 88.8888888888889
Worst: 75.49668874172185

Average Precision: 81.81958657820161
Best: 91.42857142857143
Worst: 71.25
True Positive: 1973 True Negative: 1725 False positive: 442 False negative: 360
------------------------------------------------------------------------------------------------------------------------