12. Balanced Random Forest
● Use it to train classification of scam vs. legit
● Deals with an imbalance sample (1 : 99)
13. Balanced Random Forest
● Use it to train classification of scam vs. legit
● Deals with an imbalance sample (1 : 99)
● Each tree is trained by bootstrapping a
balanced training sample
14. Balanced Random Forest
● Use it to train classification of scam vs. legit
● Deals with an imbalance sample (1 : 99)
● Each tree is trained by bootstrapping a
balanced training sample
● Aggregate the classification of each tree
15. About Shih-Ho Cheng
B.S. Physics / Math
Univ. of Virginia
Ph.D. Astro-Particle Physics
Penn State Univ.
Love board games!