feature-hashing

DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

Large Scale benchmarking of state of the art text vectorizers

Slides for my talk at PyData London 2019

FEATure HashER

Sample of Feature Hashing for Machine Learning

Our rendition of MutantX-S in python. A malware classifier employed using a prototype based clustering approach.

Local semantic-ish search across text files using feature-hashing vectors and cosine similarity (no APIs).

SKT Efficient LLM Routing Challenge — 프롬프트 텍스트만 보고 tier 별 비용 예산 안에서 ax31-light / ax31 / axk1-think 를 고르는 라우터. 파이썬 표준 라이브러리만 쓰고 평가 시점에 모델 추론을 하지 않는다. held-out dev 0.7051, 기대값 0.7043, 재표집 3,000회에서 bust 0회

Production-style ML pipeline for click-through rate prediction on the Avazu dataset. 32M training rows, 13M test predictions. L2-regularized logistic regression with smoothed CTR encoding, frequency encoding, and 2^22-dim feature hashing. Validation log loss 0.382 (~11.4% improvement over baseline).

Single-topic content categorization in pure Go — hashed char/word n-grams into a grove gradient-boosted model, one classifier per topic.

Binary text classifier in pure C++ (Feature Hashing + Logistic Regression)