<--- Back to Details
First PageDocument Content
Statistics / Statistical inference / Estimation theory / Regression analysis / Nonparametric regression / Linear regression / Machine learning / Stepwise regression / Decision tree learning / Spike-and-slab variable selection / Omnibus test
Date: 2015-10-29 18:32:57
Statistics
Statistical inference
Estimation theory
Regression analysis
Nonparametric regression
Linear regression
Machine learning
Stepwise regression
Decision tree learning
Spike-and-slab variable selection
Omnibus test

The Annals of Applied Statistics 2014, Vol. 8, No. 3, 1750–1781 DOI: AOAS755 © Institute of Mathematical Statistics, 2014 VARIABLE SELECTION FOR BART: AN APPLICATION

Add to Reading List

Source URL: www-stat.wharton.upenn.edu

Download Document from Source Website

File Size: 2,48 MB

Share Document on Facebook

Similar Documents

Practical Secure Decision Tree Learning in a Teletreatment Application Sebastiaan de Hoogh1 , Berry Schoenmakers2 , Ping Chen3 , and Harm op den Akker4 1

Practical Secure Decision Tree Learning in a Teletreatment Application Sebastiaan de Hoogh1 , Berry Schoenmakers2 , Ping Chen3 , and Harm op den Akker4 1

DocID: 1unpF - View Document

Meta–Gradient Boosted Decision Tree Model for Weight and Target Learning  Yury Ustinovskiy Valentina Fedorova Gleb Gusev Pavel Serdyukov

Meta–Gradient Boosted Decision Tree Model for Weight and Target Learning Yury Ustinovskiy Valentina Fedorova Gleb Gusev Pavel Serdyukov

DocID: 1tqdY - View Document

Decision Tree Learning  1 Decision Trees •  Tree-based classifiers for instances represented as feature-vectors.

Decision Tree Learning 1 Decision Trees •  Tree-based classifiers for instances represented as feature-vectors.

DocID: 1sy0I - View Document

Learning from uncertain data: a decision tree approach Cecília Nunes Anders Jonsson  PhySense Group

Learning from uncertain data: a decision tree approach Cecília Nunes Anders Jonsson PhySense Group

DocID: 1s4pL - View Document