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FeatureFu[l] contains a collection of library/tools for advanced feature engineering, such as using extended s-expression based feature transformation, to derive features on top of other features, or convert a light weighted model (logistical regression or decision tree) into a feature, in an intuitive way without touching any code.
Sample use cases:
Feature normalization
"(min 1 (max (+ (* slope x) intercept) 0))" : scale feature x with slope and intercept, and normalize to [0,1]
Feature combination
"(‐ (log2 (+ 5 impressions)) (log2 (+ 1 clicks)))" : combine #impression and #clicks into a smoothed CTR style feature
Nonlinear featurization
"(if (> query_doc_matches 0) 0 1)" : negation of a query/document matching feature
Cascading modeling
"(sigmoid (+ (+ (..) w1) w0))" : convert a logistic regression model into a feature
Model combination (e.g. combine decision tree and linear regression)
"(+ (* model1_score w1) (* model2_score w2))" : combine two model scores into one final score
Expr: A super fast and simple evaluator for mathematical s-expressions written in Java.