Python library for Multi-Dimensional Data Outlier/Anomaly Detection Machine Learning algorithm.
pip install mdod
git clone https://github.com/mddod/mdod.git
cd mdod
python setup.py install
import numpy as np
import mdod
localFile = 'TestDataset.txt'
dets= np.loadtxt(localFile,delimiter=',')
# nd: value of the observation point in the new dimension
nd = 1
# sn: number of statistics on the first few numbers in the order of scores from large to small
sn = 15
result = mdod.md(dets,nd,sn)
print(result)
data1,data2,data3,data4,data5,data6
data1,data2,data3,data4,data5,data6
data1,data2,data3,data4,data5,data6
...
[value1, '[data1 data2 data3 data4 data5 data6]', '0']
[value2, '[data1 data2 data3 data4 data5 data6]', '1']
[value3, '[data1 data2 data3 data4 data5 data6]', '2']
...