'Ensemble methods' presentation slideshows

On the Power of Ensemble: Supervised and Unsupervised Methods Reconciled*

1.64k views • 163 slides

The Proposed Next-Generation NCEP Production Suite

The Proposed Next-Generation NCEP Production Suite. NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems. EMC Senior Staff January 2007. Overview. Preparing for the future Production Suite: Conceptual prototype Benefits Summary. Preparing for the Future (1).

711 views • 57 slides

Supervised, semi-supervised and Unsu pervised approaches for word sense disambiguation

756 views • 56 slides

Jincong He, Louis Durlofsky, Pallav Sarma (Chevron ETC)

Jincong He, Louis Durlofsky, Pallav Sarma (Chevron ETC). Efficient Production Optimization and History Matching using Reduced Order Modeling. SUPRI-HW/Smart Fields Annual Meeting November 15-16, 2010. Reservoir Simulation Applications. Field development & operations Production optimization

754 views • 47 slides

Web-Mining Agents Ensemble Learning

474 views • 47 slides

Classification Ensemble Methods 2

Classification Ensemble Methods 2. Random forests. Given: N training samples, p variables. Algorithm: For b = 1 to B : Draw a bootstrap sample of size N from training data.

469 views • 35 slides

Weather forecasting by computer

Weather forecasting by computer. Michael Revell NIWA m.revell@niwa.co.nz. Introduction. History Operational NWP system Forecast model Data assimilation Verification Interpretation and limitations of output. NWP History. Wilhelm Bjerknes (1904)

465 views • 34 slides

Weather forecasting by computer

Weather forecasting by computer. Michael Revell NIWA m.revell@niwa.co.nz. Introduction. History Operational NWP system Forecast model Data assimilation Verification Interpretation and limitations of output. NWP History. Wilhelm Bjerknes (1904)

514 views • 34 slides

Model Evaluation

Model Evaluation. Metrics for Performance Evaluation How to evaluate the performance of a model? Methods for Performance Evaluation How to obtain reliable estimates? Methods for Model Comparison How to compare the relative performance of different models?.

616 views • 31 slides

Assimilation of Observations and Bayesianity Mohamed Jardak and Olivier Talagrand

352 views • 30 slides

Assimilation of Observations and Bayesianity Mohamed Jardak and Olivier Talagrand

303 views • 30 slides

Ensembles

Ensembles. Ensemble Methods. Ensemble methods construct a set of classifiers from the training data Predict class label of previously unseen records by aggregating predictions made by multiple classifiers In Olympic Ice-Skating you have multiple judges? Why?

339 views • 23 slides

Ensemble Methods

Ensemble Methods. An ensemble method constructs a set of base classifiers from the training data Ensemble or Classifier Combination Predict class label of previously unseen records by aggregating predictions made by multiple classifiers. General Idea. Why does it work?.

275 views • 23 slides

Data Mining

Data Mining. Ensemble Techniques Introduction to Data Mining, 2 nd Edition by Tan, Steinbach, Karpatne, Kumar. Ensemble Methods. Construct a set of classifiers from the training data Predict class label of test records by combining the predictions made by multiple classifiers.

216 views • 21 slides

Ensemble Methods and tools

Ensemble Methods and tools. Tara L. Jensen , Barbara Brown, John Halley Gotway , Tressa Fowler and Randy Bullock National Center for Atmospheric Research, Boulder Colorado, USA and Developmental Testbed Center, Boulder Colorado, USA.

353 views • 20 slides

Committee Machines the art and science of combining learning machines

Committee Machines the art and science of combining learning machines. Gavin Brown University of Birmingham g.brown@cs.bham.ac.uk http://www.cs.bham.ac.uk/~gxb/. What will we cover?. Some theory: Reasons to combine learning machines Statistics ? : Bias, Variance, and Co-variance

300 views • 15 slides

Least Squares SVM Ensemble via Diversity(Relationship) Learning

Least Squares SVM Ensemble via Diversity(Relationship) Learning. Hua Qiang. Contents. Introduction. Notation. Ensemble via Diversity Learning. Least Squares SVM. Model & Optimization. Experiment. LS-SVM Ensemble via Diversity Leaning - Introduction.

358 views • 14 slides

COMP 4332 Tutorial 6 Mar 25 CHEN Zhao

245 views • 9 slides

ZOT! To W IKIPEDI A V ANDALIS M PAN-10 @ CLEF 2010 Shared Task #2 Rebecca Maessen and James White

ZOT! To W IKIPEDI A V ANDALIS M PAN-10 @ CLEF 2010 Shared Task #2 Rebecca Maessen and James White. Data Set Low number of vandalism edits in PAN@CLEF data gave little information on patterns distinguishing vandalism from regular edits. Added 5,276 manually classified vandalism edits from

158 views • 7 slides

Mathematical/Numerical optimization

Mathematical/Numerical optimization. What are the effects of including correlated observation errors on the minimization?. How does it affect the hessian conditionning It affects the eigen spectrum. We are making the observation very accurate.

150 views • 4 slides