Presentation is loading. Please wait.

Presentation is loading. Please wait.

Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 The Goal of Classification Greg Grudic.

Published by Modified over 8 years ago

Similar presentations

Presentation on theme: "Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 The Goal of Classification Greg Grudic."— Presentation transcript:

1 Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 The Goal of Classification Greg Grudic

2 Goal of Classification Give Training Data GOAL: Construct a model Model Property: Minimum error rate on future (unseen) data: Greg GrudicIntro AI2

3 Measuring Model Accuracy: Classification Assume a set of data Classification accuracy Greg GrudicIntro AI3 Where

4 Reading For Next Class The Perceptron algorithm: –http://en.wikipedia.org/wiki/Perceptron –No need to read about the variations. Go through the Getting Started section under HELP in Matlab. Greg GrudicIntro AI4

Download ppt "Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 The Goal of Classification Greg Grudic."

Similar presentations

CS344: Introduction to Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 15, 16: Perceptrons and their computing power 6 th and.

CS344: Introduction to Artificial Intelligence Pushpak Bhattacharyya CSE Dept., IIT Bombay Lecture 15, 16: Perceptrons and their computing power 6 th and.
Decision Tree Approach in Data Mining

Decision Tree Approach in Data Mining
Data Mining Classification: Alternative Techniques

Data Mining Classification: Alternative Techniques
Greg GrudicIntroduction to AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Greg Grudic.

Greg GrudicIntroduction to AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Greg Grudic.
Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Introduction to Classification Greg Grudic.

Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202 Fall 2007 Introduction to Classification Greg Grudic.
An Introduction to Machine Learning In the area of AI (earlier) machine learning took a back seat to Expert Systems Expert system development usually consists.

An Introduction to Machine Learning In the area of AI (earlier) machine learning took a back seat to Expert Systems Expert system development usually consists.
Support Vector Machine (SVM) Classification

Support Vector Machine (SVM) Classification
1 Nearest Neighbor Learning Greg Grudic (Notes borrowed from Thomas G. Dietterich and Tom Mitchell) Intro AI.

1 Nearest Neighbor Learning Greg Grudic (Notes borrowed from Thomas G. Dietterich and Tom Mitchell) Intro AI.
Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202: The Perceptron Algorithm Greg Grudic.

Greg GrudicIntro AI1 Introduction to Artificial Intelligence CSCI 3202: The Perceptron Algorithm Greg Grudic.
7/17/2002 Greg Grudic: Nonparametric Modeling 1 High Dimensional Nonparametric Modeling Using Two-Dimensional Polynomial Cascades Greg Grudic University.

7/17/2002 Greg Grudic: Nonparametric Modeling 1 High Dimensional Nonparametric Modeling Using Two-Dimensional Polynomial Cascades Greg Grudic University.
Greg GrudicIntro AI1 Support Vector Machine (SVM) Classification Greg Grudic.

Greg GrudicIntro AI1 Support Vector Machine (SVM) Classification Greg Grudic.
Revision Michael J. Watts

Revision Michael J. Watts
Neural Networks.

Neural Networks.
Project 1: Classification Using Neural Networks 2008. 9. 24 Kim, Kwonill Biointelligence laboratory Artificial Intelligence.

Project 1: Classification Using Neural Networks Kim, Kwonill Biointelligence laboratory Artificial Intelligence.
Evaluating Hypotheses Reading: Coursepack: Learning From Examples, Section 4 (pp. 16-21)

Evaluating Hypotheses Reading: Coursepack: Learning From Examples, Section 4 (pp )
Matlab Matlab Sigmoid Sigmoid Perceptron Perceptron Linear Linear Training Training Small, Round Blue-Cell Tumor Classification Example Small, Round Blue-Cell.

Matlab Matlab Sigmoid Sigmoid Perceptron Perceptron Linear Linear Training Training Small, Round Blue-Cell Tumor Classification Example Small, Round Blue-Cell.
From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic.

From Machine Learning to Deep Learning. Topics that I will Cover (subject to some minor adjustment) Week 2: Introduction to Deep Learning Week 3: Logistic.
George F Luger ARTIFICIAL INTELLIGENCE 6th edition Structures and Strategies for Complex Problem Solving Machine Learning: Connectionist Luger: Artificial.

George F Luger ARTIFICIAL INTELLIGENCE 6th edition Structures and Strategies for Complex Problem Solving Machine Learning: Connectionist Luger: Artificial.
The Perceptron. Perceptron Pattern Classification One of the purposes that neural networks are used for is pattern classification. Once the neural network.

The Perceptron. Perceptron Pattern Classification One of the purposes that neural networks are used for is pattern classification. Once the neural network.
AI – CS289 Machine Learning - Labs Machine Learning – Lab 4 02 nd November 2006 Dr Bogdan L. Vrusias

AI – CS289 Machine Learning - Labs Machine Learning – Lab 4 02 nd November 2006 Dr Bogdan L. Vrusias

Similar presentations

Ads by Google