'Model based approach' diaporamas de présentation

Tight Clustering: a method for extracting stable and tight patterns in expression profiles

Tight Clustering: a method for extracting stable and tight patterns in expression profiles. A class of penalized and weighted K-means for clustering. George C. Tseng Dept. of Biostatistics & Human Genetics University of Pittsburgh. Image analysis. Normalization. Identify differentially

526 views • 52 slides

Cluster Analysis for Gene Expression Data

499 views • 35 slides

Session 2: Modelling Social Segregation Monday 30 th June 2008

Modelling Segregation Using Multilevel Models: FSM in England 2001-6. Session 2: Modelling Social Segregation Monday 30 th June 2008. Outline. Motivation: the importance of segregation Research questions Data: FSM obtained from PLASC Traditional index approaches

467 views • 32 slides

Session 2: Modelling Social Segregation Monday 30 th June 2008

Modelling Segregation Using Multilevel Models: FSM in England 2001-6. Session 2: Modelling Social Segregation Monday 30 th June 2008. Outline. Motivation: the importance of segregation Research questions Data: FSM obtained from PLASC Traditional index approaches

323 views • 32 slides

Session 2: Modelling Social Segregation Monday 30 th June 2008

Modelling Segregation Using Multilevel Models: FSM in England 2001-6. Session 2: Modelling Social Segregation Monday 30 th June 2008. Outline. Motivation: the importance of segregation Research questions Data: FSM obtained from PLASC Traditional index approaches

321 views • 32 slides

Fault Detection in a Continuous Pulp Digester

P. C. M. Fault Detection in a Continuous Pulp Digester. P. Dufour, S. Bhartiya, T.J. English, E.P. Gatzke, P.S. Dhurjati and F.J. Doyle III. Motivation Digester Operation and Faults Fault Detection Techniques NL dynamic gross error detection Abnormal event detection with ANN

464 views • 29 slides

Fault Detection in a Continuous Pulp Digester

P. C. M. Fault Detection in a Continuous Pulp Digester. P. Dufour, S. Bhartiya, T.J. English, E.P. Gatzke, P.S. Dhurjati and F.J. Doyle III. Motivation Digester Operation and Faults Fault Detection Techniques NL dynamic gross error detection Abnormal event detection with ANN

417 views • 29 slides

Background

HYBRIDIZED DECISION APPROACH FOR FAULT DIAGNOSIS OF COMPLEX INDUSTRIAL PROCESSES - Yuba Raj Adhikari Department of Electrical Engineering, Pulchwok Campus,(IOE-TU). Background. Industrial processes complex processes a lot of measurments or information available.

382 views • 22 slides

Background

HYBRIDIZED DECISION APPROACH FOR FAULT DIAGNOSIS OF COMPLEX INDUSTRIAL PROCESSES - Yuba Raj Adhikari Department of Electrical Engineering, Pulchwok Campus,(IOE-TU). Background. Industrial processes complex processes a lot of measurments or information available.

438 views • 22 slides

Learning-based methods to MDP and POMDP (Reinforcement learning & Q-Learning)

Learning-based methods to MDP and POMDP (Reinforcement learning & Q-Learning). Presented by, Niketan Pansare ( np6@rice.edu ) Rice University. Outline. - Reinforcement Learning - Exploration-Exploitation tradeoff - Q-Learning and SARSA - Learning-based methods to POMDP

426 views • 20 slides

Research on Improvements to Current SIPP Imputation Methods

Research on Improvements to Current SIPP Imputation Methods. ASA-SRM SIPP Working Group September 16, 2008 Martha Stinson. Census Imputation Research Plan. Few changes made to actual production imputation methods in many years

363 views • 19 slides