September 25th, 2013

Gradient Boosting Machine in III Acts: Trevor Hastie, Netflix & 0xdata

RSS icon RSS Category: Uncategorized [EN]
Fallback Featured Image

Gradient Boosting Machine in III Acts: Dr. Trevor Hastie, Netflix & 0xdata. Triple Header on Boosting & GBM:
Act I: Trevor Hastie, Of Stanford Mathematical Sciences, the mathematician behind Lasso & GBM speaks of the nuances of the Algorithm.
Act II: Cliff Click, CTO of 0xdata, the implementor of parallel and distributed GBM.
Act III: Antonio Molins, Data Scientist at Netflix, who uses GBM in his practice of data science for Marketing Algorithmic Models.
Boosting is a simple strategy that produces dramatic improvement in prediction performance. It works by sequentially applying a Classification Algorithm to reweighted versions of training data and taking the weighted majority vote of the sequence of classifiers produced.

“In the last 10 years my colleagues and I have been drawn into the machine learning domain, probably after the lure of neural networks. This has led us to offer a statistical perspective on novel and popular techniques arising outside of statistics, such as boosting and support-vector machines. This culminated in our 2001 book “Elements of Statistical Learning”, but the interest continues.”
-Trevor Hastie, http://www.stanford.edu/~hastie

GBM Implementation:

H2O https://github.com/0xdata/h2o/tree/master/src/main/java/hex/gbm
R: http://cran.r-project.org/web/packages/gbm/gbm.pdf<

References:

http://www.stanford.edu/~hastie/Papers/AdditiveLogisticRegression/alr.pdf

Leave a Reply

+
10 Consejos para Convertirte en un Científico de Datos Exitoso

En este mundo que no deja de cambiar y sorprendernos, como científicos de datos debemos

January 19, 2023 - by Favio Vázquez
+
Explaining models built in H2O-3 — Part 1

Machine Learning explainability refers to understanding and interpreting the decisions and predictions made by a

December 22, 2022 - by Parul Pandey
+
H2O.ai at NeurIPS 2022

H2O.ai is proud to participate in the 36th Conference on Neural Information Processing Systems (NeurIPS)

December 6, 2022 - by Marcos V. Conde
+
A Brief Overview of AI Governance for Responsible Machine Learning Systems

Our paper “A Brief Overview of AI Governance for Responsible Machine Learning Systems” was recently

November 30, 2022 - by Navdeep Gill, Abhishek Mathur and Marcos V. Conde
+
H2O World Dallas Customer Talks

After three long years of not having an #H2OWorld, we finally held our first one

November 24, 2022 - by Vinod Iyengar
+
New in Wave 0.24.0

Another Wave release has arrived with quite a few exciting new features. Let's quickly go

November 21, 2022 - by Martin Turoci

Request a Demo

Explore how to Make, Operate and Innovate with the H2O AI Cloud today

Learn More