A gradient boosting approach to the Kaggle load forecasting competition

Souhaib Ben Taieb1 and Rob J Hyndman2

1 Machine Learning Group, Department of Computer Science, Faculty of Sciences, Universit´e Libre de Bruxelles

更多

2 Department of Econometrics and Business Statistics, Monash University, Clayton, VIC 3800, Australia

收起

Winning the Kaggle Algorithmic Trading Challenge with the Composition of Many Models and Feature Engineering

Ildefons Magrans de Abril

Tokyo Institute of Technology, Japan.

更多

ildefons@sg.cs.titech.ac.jp

Masashi Sugiyama

Tokyo Institute of Technology, Japan.

sugi@cs.titech.ac.jp

http://sugiyama-www.cs.titech.ac.jp/˜sugi

收起

TITANIC: INTRODUCTION TO ONLINE COMPETITIONS ON KAGGLE.COM

ABSTRACT

Step-by-step guide to competing on Kaggle.com using “Titanic” challenge as an example. The guide is prepared by undergraduate students majoring in Economics at Rice University for undergraduate students in Social Sciences.

更多

Instructor: Natalia Sizova

Rice University

收起

Beating Kaggle the easy way

Studienarbeit

Ying Dong

更多

Wirtschaftsinformatik

收起

Beginner’s guide to Machine Learning competitions

Christine Doig

Introduction to data analysis with Python and R in Kaggle

Statistical methods for data analysis – Machine learning

Alberto Castellini

更多

University of Verona

收起

Climbing the Kaggle Leaderboard by Exploiting the Log-Loss Oracle

Jacob Whitehill (jrwhitehill@wpi.edu)

Worcester Polytechnic Institute

Kaggle Competition: Product Classification

Machine Learning CS933

Term Project

更多

Name:

Muping He

Jianan Duan

Sinian Zheng

收起