tks0123456789 / kaggle-Walmart_Trip_Type
15th solution for Walmart Recruiting: Trip Type Classification
☆12Updated 9 years ago
Alternatives and similar repositories for kaggle-Walmart_Trip_Type:
Users that are interested in kaggle-Walmart_Trip_Type are comparing it to the libraries listed below
- R script for Otto Group Production Classification on Kaggle☆28Updated 9 years ago
- ☆23Updated 8 years ago
- ☆30Updated 8 years ago
- 12th solution for the Otto Group Product Classification Challenge on Kaggle☆48Updated 9 years ago
- FirePlug: A plug to multiple remote Docker hosts (PoC & experimental)☆11Updated 8 years ago
- Top15 Model for Kaggle-Competition "Homesite Quote Conversion"☆46Updated 8 years ago
- Code for RECRUIT Challenge. 5th place.☆66Updated 9 years ago
- kaggle walmart-recruiting-sales-in-stormy-weather☆47Updated 9 years ago
- Scikit-learn API toy wrapper for Regularized Greedy Forests☆44Updated 8 years ago
- Recruit Restaurant Visitor Forecasting 25th place solution☆12Updated 7 years ago
- ☆26Updated 9 years ago
- Python Implementation of Feature Extraction with K-Nearest Neighbor☆64Updated last year
- Homesite Kaggle☆30Updated 9 years ago
- Winning solution scripts☆53Updated 7 years ago
- Stochastic Dummy Boosting☆24Updated 8 years ago
- ☆24Updated 10 years ago
- 44th place solution in "Santander Customer Satisfaction"☆10Updated 8 years ago
- Support Vector Machine (SVM) implementation using Chainer☆25Updated 9 years ago
- ☆26Updated 8 years ago
- ☆28Updated 7 years ago
- Kaggle Otto Group Product Classification Challenge☆34Updated 9 years ago
- ☆9Updated 8 years ago
- Kaggle Seizure Prediction Competition☆21Updated 8 years ago
- Python code for tree ensemble interpretation☆83Updated 4 years ago
- Deep Networks with Stochastic Depth implementation by Chainer☆40Updated 8 years ago
- Kaggle 'Search Results Relevance' 2nd place solution☆79Updated 9 years ago
- solution of our team Dmitry&Leustagos for Amazon competition (3rd place)☆31Updated 11 years ago
- lightgbmのfeature-transform(特徴量の非 線形化)をすることで、80,000を超える特徴量を線形回帰でも表現できることを示します☆11Updated 7 years ago
- A Kaggle competition (Rank 37 solution)☆10Updated 5 years ago
- programs about machine learning☆23Updated 7 years ago