Knowledge Management

Help with ML finding RCA from dimensions

kuzkuz
Explorer

Hello, first steps with ML, appreciate guidance on which ML method to use to get started.

We have a set of metrics marked as Good\Bad and we want to identify a probable root cause based on the various dimensions.

  • See below CSV example, there are 2 entries with bad values for metric "health"
  • There are multiple dimensions OS, Server, Storage
  • in this case the root cause is OS = Win7, which is easy to point out

What ML method can be used to provide the correct result?

Thanks!

Name,metric_name,result,OS,Server,Storage
PC-1,health,good,Win10,Server1,S1
PC-2,health,good,Win10,Server2,S1
PC-3,health,good,Win10,Server3,S1
PC-4,health,good,Win10,Server1,S1
PC-5,health,good,Win10,Server2,S1
PC-6,health,good,Win10,Server3,S2
PC-7,health,good,Win10,Server1,S2
PC-8,health,good,Win10,Server2,S2
PC-9,health,bad,Win7,Server3,S2
PC-10,health,bad,Win7,Server1,S2

0 Karma
1 Solution

hkeswani_splunk
Splunk Employee
Splunk Employee

Predict Categorical Assistant could be applied on this straight ahead using MLTK or you can use classifier algorithms like Random Forest Classifier directly via spl.

View solution in original post

0 Karma

hkeswani_splunk
Splunk Employee
Splunk Employee

Predict Categorical Assistant could be applied on this straight ahead using MLTK or you can use classifier algorithms like Random Forest Classifier directly via spl.

0 Karma
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