PPT-Generalizing Linear Discriminant Analysis

Linear Discriminant Analysis Objective Project a feature space a dataset ndimensional samples onto a smaller Maintain the class separation Reason Reduce computational costs Minimize . PCA Limitations of LDA Variants of LDA Other dimensionality reduction methods brPage 2br CSCE 666 Pattern Analysis Ricardo Gutierrez Osuna CSETAMU Linear discriminant analysis two classes Objective LDA seeks to reduce dimensionality while preserv N is the process noise or disturbance at time are IID with 0 is independent of with 0 Linear Quadratic Stochastic Control 52 brPage 3br Control policies statefeedback control 0 N called the control policy at time roughly speaking we choo a 12 22 a a mn is an arbitrary matrix Rescaling The simplest types of linear transformations are rescaling maps Consider the map on corresponding to the matrix 2 0 0 3 That is 7 2 0 0 3 00 brPage 2br Shears The next simplest type of linear transfo Fisher Linear Discriminant 2 Multiple Discriminant Analysis brPage 2br CSE 555 Srihari 1 Motivation Projection that best separates the data in a least squares sense CA finds components that are useful for representing data owever no reason to assum ECE, UA. Content. Introduction. Support Vector Machines. Active Learning Methods. Experiments & Results. Conclusion. Introduction. ECG signals represent a useful information source about the rhythm and functioning of the heart.. I. Standard Form of a quadratic. In form of . Lead coefficient (a) is positive..  .  .  . Examples.  . II. Discriminant. Tells us about nature . of. roots of a quadratic. 4 cases: 1. If D>0, then 2 real roots.. Why do we use the discriminant?. The discriminant tells us one of two things:. How many roots/x-intercepts/zeros does a quadratic function have?. How many solutions does a quadratic equation have?. Example. This PowerPoint . was adapted from . http://. www.purplemath.com/modules/quadform2.htm. and . http://. teachers.henrico.k12.va.us/math/hcpsalgebra2/Documents/6-4/2006_6_4.ppt. Looking Back…. In our previous lesson, we solved quadratic function by . Dr J Frost (jfrost@tiffin.kingston.sch.uk) . Last modified: . 23. rd. August . 2015. Objectives: . Understand the conditions under which a quadratic equation has no, equal or distinct roots.. STARTER. Defining and Testing Groups. Goals. Develop classificatory key for groups that have already been defined. Identify important variables in defining clusters after cluster analysis. Classify new observations into an existing classification. Recall, we have used the quadratic formula previously. Gives the location of the roots (x-intercepts) of the graph of a parabola. Function must be in standard form; f(x) = ax. 2. + . bx. + c. Example. Find the roots for the function f(x) = 2x. ECE, UA. ECG signal processing - Case [1]. Diagnosis of Cardiovascular Abnormalities From Compressed ECG: A Data Mining-Based Approach[1]. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 15, NO. 1, JANUARY 2011. CS 560 Artificial Intelligence. Many slides throughout the course adapted from Svetlana . Lazebnik. , Dan Klein, Stuart Russell, Andrew Moore, Percy Liang, Luke . Zettlemoyer. , Rob . Pless. , Killian Weinberger, Deva . Mohammad Ali . Keyvanrad. Machine Learning. In the Name of God. Thanks to: . M. . . Soleymani. (Sharif University of Technology. ). R. . Zemel. (University of Toronto. ). p. . Smyth . (University of California, Irvine).