I believe by default the Machine Learning Toolkit utilizes one hot encoding when converting categorical variables to numerical. Is there an easy way to utilize label encoding? For example - I want to assign a risk score based on country. So China may map to a 5 and US may map to a 1, where 5 is riskier than 1.
I imagine I could do this with a bunch of eval commands in the query or alternatively an additional field extract, but is there a "prettier" way to do this?
One option, if the scores are relatively static, is to use a lookup. Another option, if you've calculated all the 'risk_score's and want to keep them "up to date" as conditions change, is to use a regression model:
... | fit LinearRegression risk_score from factor_A factor_B ... into my_risk_model
You could use whatever regression algorithm you want and whatever factors you want. Then, when it's time to score: