I would like to make a flow chart for an ML classifier and make sure that my thinking is correct.

Here is a little about my sample: I have 3 classes and about 160 features. I suspect that some of those features are redundant. My classes are imbalanced. Please let me know if I should provide more info about the sample.

This is my first try on tackling a machine learning problem. Based on checking the functionality of each of the options I use below, I chose it in that specific order, but i might be wrong.

Could someone just let me know if this flow chart is logical, and if there was a problem in any of the step, could you possible tell me why it is not supposed to be there?

Flow chart

  1. Get the data
  2. Make it in a readable format and import it
  3. Split the data into train/test
  4. Standardize with StandardScalar
  5. Perform PCA on train data
  6. Perform K-fold cross-validation on train data
  7. Apply SMOTE
  8. Predict (Using SVC)
  9. Make a confusion matrix
  10. Perform GridSearchCV
  11. Perform PermutationImportance

closed as primarily opinion-based by oW_, Stephen Rauch, user12075, Sean Owen Sep 16 '18 at 2:30

Many good questions generate some degree of opinion based on expert experience, but answers to this question will tend to be almost entirely based on opinions, rather than facts, references, or specific expertise. If this question can be reworded to fit the rules in the help center, please edit the question.

  • $\begingroup$ The flow chart you have given looks complete to me. $\endgroup$ – Akhilesh Pandey Sep 14 '18 at 9:44
  • $\begingroup$ Thank you very much for your reply, wanted to know if it is in proper order. $\endgroup$ – tsumaranaina Sep 17 '18 at 0:20
  • $\begingroup$ Just got a note that the standardization should happen on the data that is already split to avoid data leakage.. Still need a confirmation. $\endgroup$ – tsumaranaina Sep 19 '18 at 0:16