- XGboost: gradient boosted trees를 사용해 classification
- SVM: data에서 가장 멀리 떨어진 hyper-planes를 만들어 classification
- Neural network with entity embedding: categorical features를 차원 축소해 NN 사용
- Collaborative filtering: 학습된 벡터 중 가장 가까운 벡터를 찾아 추천해주는 기법
- Linear regression: 단순한 linear model를 사용해서 더 좋은 결과가 나오는 경우 있음
- Tensorflow, Keras, scikit-learn library 등을 활용
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