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Search: LightGBM
Page 15
Showing 10 results from 269
ffRunKey/lightgbm_BiLSTM
GitHub MIT LicenseA Study on Stock Price Prediction and Quantitative Strategy - Based on Deep Learning 『深層学習に基づく株価予測とクオンツ戦略に関する研究』基于深度学习的股票价格预测和量化策略研究
External source
GitHub
Y-oHr-N/OptGBM
GitHub Python MIT LicenseOptuna + LightGBM = OptGBM
External source
GitHub
rishiraj/autolgbm
GitHub Python Apache License 2.0LightGBM + Optuna: Auto train LightGBM directly from CSV files, Auto tune them using Optuna, Auto serve best model using FastAPI. Inspired by Abhishek Thakur's AutoXGB.
External source
GitHub
4paradigm/DemoApps
GitHub Python Apache License 2.0demo applications that show how to deploy offline feature engineering solutions to online in one minute with fedb and nativespark
External source
GitHub
TomerRonen34/treeboost_autograd
GitHub Python MIT LicenseEasy Custom Losses for Tree Boosters using Pytorch
External source
GitHub
LenzDu/Kaggle-Competition-Sberbank
GitHub Python MIT LicenseTop 1% rankings (22/3270) code sharing for Kaggle competition Sberbank Russian Housing Market: https://www.kaggle.com/c/sberbank-russian-housing-market
External source
GitHub
ZongXR/DCIC2024-PhotoVoltaic
GitHub Jupyter Notebook GNU General Public License v3.0本赛题要求选手基于历史光伏发电数据、天气数据、光伏设备空间相对位置等信息,通过建立适当的模型,对未来一段时间内的光伏发电出力进行预测。A榜使用外部数据得分0.88501103804 排名32,未使用外部数据得分0.88042407737 ;B榜得分0.90467829011排名21.
External source
GitHub
microsoft/lightgbm-transform
GitHub C++ MIT LicenseTransformation library for LightGBM
External source
GitHub
angelotc/LightGBM-binary-classification-example
GitHub Jupyter NotebookA model that predicts the default rate of credit card holders using the LightGBM classifier. Trained the LightGBM classifier with Scikit-learn's GridSearchCV.
External source
GitHub
buus2/dcbit
GitHub Jupyter NotebookDemo from Data Community Bydgoszcz i Toruń, 27.02.2019
External source
GitHub
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Showing first 269 accessible GitHub results.