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» VIF Regression: A Fast Regression Algorithm for Large Data
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ICDM
2009
IEEE
146views Data Mining» more  ICDM 2009»
14 years 28 days ago
Induction of Mean Output Prediction Trees from Continuous Temporal Meteorological Data
: In this paper, we present a novel method for fast data-driven construction of regression trees from temporal datasets including continuous data streams. The proposed Mean Output ...
Dima Alberg, Mark Last, Roni Neuman, Avi Sharon
KDD
2002
ACM
118views Data Mining» more  KDD 2002»
14 years 6 months ago
SECRET: a scalable linear regression tree algorithm
Recently there has been an increasing interest in developing regression models for large datasets that are both accurate and easy to interpret. Regressors that have these properti...
Alin Dobra, Johannes Gehrke
JMLR
2002
106views more  JMLR 2002»
13 years 6 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
NIPS
2007
13 years 7 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
CSDA
2011
12 years 9 months ago
Iterative stepwise regression imputation using standard and robust methods
Imputation of missing values is one of the major tasks for data pre-processing in many areas. Whenever imputation of data from official statistics comes into mind, several (additi...
Matthias Templ, Alexander Kowarik, Peter Filzmoser