Modeling Hospitalization Outcomes with Random Decision Trees and Bayesian Feature Selection Thomson Van Nguyen† Bhubaneswar Mishra†

First Page		Document Content
Date: 2011-09-15 16:45:15 Ensemble learning Econometrics Model selection Cross-validation Bootstrap aggregating Training set Linear regression Random forest Feature selection Statistics Regression analysis Machine learning		Modeling Hospitalization Outcomes with Random Decision Trees and Bayesian Feature Selection Thomson Van Nguyen† Bhubaneswar Mishra† Add to Reading List Source URL: ftp.cs.nyu.edu Download Document from Source Website File Size: 325,02 KB Share Document on Facebook

	Linear Regression Kalman Filtering Based on Hyperspherical Deterministic Sampling Gerhard Kurz and Uwe D. Hanebeck Abstract— Nonlinear filtering based on Gaussian densities is commonly performed using so-called Linear DocID: 1vq9G - View Document
	Source and Channel Codes via Sparse Linear Regression Ramji Venkataramanan Sekhar Tatikonda DocID: 1v5oo - View Document
	Pattern Recognition And Machine Learning - EPFL - Fall 2015 Emtiyaz Khan, Timur Bagautdinov, Carlos Becker, Ilija Bogunovic & Ksenia Konyushkova 2. Linear Regression and Gradient Descent 2.1 DocID: 1v534 - View Document
	Flexible Covariate Adjustments in Randomized Experiments Christoph Rothe Abstract: Linear regression adjustments for pre-treatment covariates are widely used in economics to lower the variance of treatment effect estimat DocID: 1uYMC - View Document
	C ONTRIBUTED RESEARCH ARTICLE 232 liureg: A Comprehensive R Package for the Liu Estimation of Linear Regression DocID: 1uFMP - View Document