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adult
adult
 
 
data
data
 
 
iris
iris
 
 
nsl_kdd
nsl_kdd
 
 
ranking
ranking
 
 
sample
sample
 
 
unsw
unsw
 
 
wine
wine
 
 
wsn
wsn
 
 
README.md
README.md
 
 
adult_feature.py
adult_feature.py
 
 
adult_score.py
adult_score.py
 
 
apriori.py
apriori.py
 
 
category.py
category.py
 
 
discretization.py
discretization.py
 
 
fp_growth.py
fp_growth.py
 
 
iris_feature.py
iris_feature.py
 
 
iris_score.py
iris_score.py
 
 
kdd_rule_combine.py
kdd_rule_combine.py
 
 
kdd_rule_feature.py
kdd_rule_feature.py
 
 
kdd_rule_pred.py
kdd_rule_pred.py
 
 
kdd_rule_score.py
kdd_rule_score.py
 
 
kdd_transform_attack.py
kdd_transform_attack.py
 
 
lab_feature.py
lab_feature.py
 
 
load.py
load.py
 
 
log.md
log.md
 
 
max_sup_freq_rule.py
max_sup_freq_rule.py
 
 
old_discretization.py
old_discretization.py
 
 
prepare.py
prepare.py
 
 
preprocess.py
preprocess.py
 
 
random_sample.py
random_sample.py
 
 
raw.py
raw.py
 
 
rule.py
rule.py
 
 
rule_feature.py
rule_feature.py
 
 
rule_feature_pred.py
rule_feature_pred.py
 
 
rule_num_feature_score.py
rule_num_feature_score.py
 
 
rule_one_dimension_feature.py
rule_one_dimension_feature.py
 
 
rule_one_dimension_score.py
rule_one_dimension_score.py
 
 
rule_score.py
rule_score.py
 
 
rule_second_feature.py
rule_second_feature.py
 
 
rule_second_feature_pred.py
rule_second_feature_pred.py
 
 
rule_train_pred.py
rule_train_pred.py
 
 
rule_train_seconde_feature.py
rule_train_seconde_feature.py
 
 
set.py
set.py
 
 
set_discretize.py
set_discretize.py
 
 
split_ok.py
split_ok.py
 
 
t.py
t.py
 
 
test.py
test.py
 
 
train.py
train.py
 
 
train_test_rule.py
train_test_rule.py
 
 
value_map_table.py
value_map_table.py
 
 
wine_feature.py
wine_feature.py
 
 
wine_score.py
wine_score.py
 
 

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IDS

The backup data set for the research in 2017.

  • Language: Python 2
  • Package: Pandas, Scikit-learn

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For my research only.

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