: 2019-06-05 03:38:06
Description: data set ns-kdd
The above dataset requires a preprocessing process to run decision tree algorithm and genetic algorithms in the following phases:
1. Removing null values: To remove null values, these values were replaced by mean values of the same feature in the dataset.
2. Normalizing features: Due to the fact that the range of feature values varies and they differ greatly, the range of these values must be homogeneous to improve the performance of machine learning algorithms, which was also applied to the dataset. Z-score  was used to normalize the features.
screePlot.py, 8098 , 2017-06-14
all-featuers.py, 8979 , 2017-12-29
Genetic.py, 12913 , 2017-12-29
plot_roc.py, 17171 , 2017-06-15
KDDTest%2B.csv, 2661842 , 2017-06-14
KDDTest-21.csv, 1419963 , 2017-06-14
KDDTrain.mat.ods, 16499500 , 2019-01-17
KDDTrain%2B.csv, 14738831 , 2019-01-17