'Bias variance' diaporamas de présentation

Object Detection with Statistical Template

Object Detection with Statistical Template. Computer Vision Jia-Bin Huang, Virginia Tech. Many slides from D. Hoiem, J. Hays. Administrative stuffs. HW 5 is out Due 11:59pm on Wed, November 16 Scene categorization Please s tart early Final project proposal Feedback via email s.

1.03k views • 102 slides

xkcd/242/

http://xkcd.com/242/. Text Classification 2. David Kauchak cs160 Fall 2009 adapted from: http://www.stanford.edu/class/cs276/handouts/ lecture10-textcat-naivebayes.ppt http://www.stanford.edu/class/cs276/handouts/lecture11-vector-classify.ppt

831 views • 66 slides

Photo by Carl Warner

Photo by Carl Warner. Photo by Carl Warner. Photo by Carl Warner. 09/26/11. Machine Learning: Classification. Computer Vision CS 143, Brown James Hays. Slides from Lazebnik , Hoiem , and others. The machine learning framework.

845 views • 52 slides

Photo by Carl Warner

Photo by Carl Warner. Photo by Carl Warner. Photo by Carl Warner. 09/26/11. Machine Learning: Classification. Computer Vision CS 143, Brown James Hays. Slides from Lazebnik , Hoiem , and others. The machine learning framework.

525 views • 52 slides

Machine Learning

569 views • 50 slides

Classifiers

721 views • 48 slides

Bias-Variance in Machine Learning

Bias-Variance in Machine Learning. Bias-Variance: Outline. Underfitting/overfitting: Why are complex hypotheses bad? Simple example of bias/variance Error as bias+variance for regression brief comments on how it extends to classification Measuring bias, variance and error

473 views • 46 slides

Quiz 1 on Wednesday

Quiz 1 on Wednesday. ~20 multiple choice or short answer questions In class, full period Only covers material from lecture, with a bias towards topics not covered by projects Study strategy: Review the slides and consult textbook to clarify confusing parts. Project 3 preview.

466 views • 46 slides

Bias and Variance of the Estimator

Bias and Variance of the Estimator. PRML 3.2 Ethem Chp. 4. In previous lectures we showed how to build classifiers when the underlying densities are known Bayesian Decision Theory introduced the general formulation

395 views • 35 slides