CS699 Lecture 4 Classification 1 Supervised vs. Unsupervised Learning Supervised learning (classification) Supervision: The training data (observations, measurements, etc.) are accompanied by class labels indicating the class of the observations New data is classified based on the training set Unsupervised learning (clustering) The class labels of training data is unknown […]
Due: 3/22 Note: Show all your work. Assignment 7 Problem 1 (10 points) This question is about a learning classifier system XCS that we discussed in the class. Consider the following population, which has the current set of rules: 1101 01 1#1# 01 1#0# 01 #0#1 10 #01# 10 10#1 10 1011 01 Suppose that
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CS699 Lecture 5 Classification 2 • Using IF‐THEN Rules for Classification Represent the knowledge in the form of IF‐THEN rules • Assessment of a rule: coverage and accuracy – A tuple is covered by R if it satisfies the antecedent of R – ncovers = # of tuples covered by R – ncorrect = #
CS699 Lecture 1 Introduction • Our focus is “data mining” not “data warehousing.” • Will discuss – Data preprocessing CS699 • Data mining is an important component of data analysis. – Basic data mining algorithms – How to evaluate data mining models and data mining results – How to perform data mining using software tools
Data Structures and Algorithms Chapter 2 Inheritance • Inheritance hierarchy example ArithmeticProgression # increment: long # advance() GeometricProgression # base: long # advance() FibonacciProgression # prev: long # advance() Inheritance Progression # current: long + nextValue(): long + printProgression(n: int) # advance() Inheritance /* not a complete code */ public class Progression { } protected
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Data Structures and Algorithms Chapter 3 Linked Lists • A node stores an element and a link (or links). • Nodes are connected by links. • A link is the reference to (or the address of) a node. • Singly linked list, doubly linked list, circularly linked list • Link, reference, and pointer are used
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3/23/21 CSE 473/573 Introduction to Computer Vision and Image Processing ‘- SEGMENTATION QUESTIONS REGARDING ANYTHING? Slides: James Hays Isabelle Guyon, Erik Sudderth, Mark Johnson, Derek Hoiem ‘- 1 3/23/21 Image Segmentation • Segmentation attempts to partition the pixels of an image into groups that strongly correlate with the objects in an image • Typically the
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CS699 Lecture 10 Clustering What is Cluster Analysis? Cluster: A collection of data objects similar (or related) to one another within the same group dissimilar (or unrelated) to the objects in other groups Cluster analysis (or clustering, data segmentation, …) Finding similarities between data according to the characteristics found in
Data Structures and Algorithms Chapter 1 Java Basics Sample Program Java Basics Components of a Java Program • In Java, executable statements are placed in functions, known as methods, that belong to class definitions. • The static method named main is the first method to be executed when running a Java program. • Any set
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3/30/2021 CSE 473/573 ‘- Introduction to Computer Vision and Image Processing 1 Using K-NN • Simple, a good one to try first • With infinite examples, 1-NN provably has error that is at most twice Bayes optimal error 2 ‘- 1 3/30/2021 Sec. 15.1 Support Vector Machine (SVM) • SVMs maximize the margin around the
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