machine learning normalizing data
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i need to predict supervisory post grade in a group of organization.The supervisory post have subordinates with lower grade( G1 to G10). The goal to input the subordinates grade and job family(occ).The output should predict supervisory(Head) grade and level.
example of a group in organization:
OCC TITLE GRADE Level
0510 Head cost control E 2 <-----predict this
0510 Sr. Accountant P 6 <------input
0510 Accountant P 5 <-----input
0503 Financial specialist G 9 <-----input
OCC is a category not numerical, so what is the best way to form the matrix and prepare in the datasets to have a normalized data? currently I am working with classification learner.
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Aditya Patil
2020 年 8 月 17 日
I understand that you want to consider OCC as categorical data. Use the categorical function to create a categorical array from a numerical array.
For example,
occ = [0510, 0510, 0510, 0503];
occ_cat = categorical(occ);
Then use the this array in classification learner app.
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