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  • Discriminant Function Old Kiwi
    ...ots, w_k</math> and feature vector x, which is in n-dimensional space, the discriminant functions <math>g_1(x), g_2(x), \ldots, g_k(x)</math> where <math>g_\#(x)</ Discriminant functions are used to define [[Decision Surfaces_Old Kiwi]].
    548 B (89 words) - 08:53, 10 April 2008
  • Discriminant function Old Kiwi
    #REDIRECT: [[discriminant Function_Old Kiwi]]
    45 B (5 words) - 10:54, 17 March 2008

Page text matches

  • ECE662:BoutinSpring08 Old Kiwi
    * [[Lecture 5 - Discriminant Functions_Old Kiwi]] * [[Lecture 6 - Discriminant Functions_Old Kiwi]]
    6 KB (747 words) - 04:18, 5 April 2013
  • ECE662:Glossary Old Kiwi
    Bayes' decision rule creates an objective function which minimizes the probability of error (misclassification). This method a Refers to the problem caused by exponential growth of hypervolume as a function of dimensionality. This term was coined by Richard Bellman in 1961.
    31 KB (4,832 words) - 17:13, 22 October 2010
  • Lecture 17 - Nearest Neighbors Clarification Rule and Metrics Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (938 words) - 07:38, 17 January 2013
  • Lecture 1 - Introduction Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    3 KB (468 words) - 07:45, 17 January 2013
  • Lecture 2 - Decision Hypersurfaces Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (737 words) - 07:45, 17 January 2013
  • Lecture 3 - Bayes classification Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (843 words) - 07:46, 17 January 2013
  • Lecture 5 - Discriminant Functions Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (916 words) - 07:47, 17 January 2013
  • Lecture 6 - Discriminant Functions Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    9 KB (1,586 words) - 07:47, 17 January 2013
  • Lecture 7 - MLE and BPE Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    10 KB (1,488 words) - 09:16, 20 May 2013
  • Lecture 8 - MLE, BPE and Linear Discriminant Functions Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (792 words) - 07:48, 17 January 2013
  • Lecture 9 - Linear Discriminant Functions Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,307 words) - 07:48, 17 January 2013
  • Lecture 10 - Batch Perceptron and Fisher Linear Discriminant Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (755 words) - 07:48, 17 January 2013
  • Lecture 11 - Fischer's Linear Discriminant again Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (907 words) - 07:49, 17 January 2013
  • Lecture 12 - Support Vector Machine and Quadratic Optimization Problem Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,235 words) - 07:49, 17 January 2013
  • Lecture 13 - Kernel function for SVMs and ANNs introduction Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,354 words) - 07:51, 17 January 2013
  • Lecture 14 - ANNs, Non-parametric Density Estimation (Parzen Window) Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    13 KB (2,073 words) - 07:39, 17 January 2013
  • Lecture 15 - Parzen Window Method Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    7 KB (1,212 words) - 07:38, 17 January 2013
  • Lecture 16 - Parzen Window Method and K-nearest Neighbor Density Estimate Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    10 KB (1,607 words) - 07:38, 17 January 2013
  • Lecture 18 - Nearest Neighbors Clarification Rule and Metrics(Continued) Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (1,066 words) - 07:40, 17 January 2013
  • Support Vector Machines Old Kiwi
    ...ratic Optimization Problem_Old Kiwi|Lecture 12]] and [[Lecture 13 - Kernel function for SVMs and ANNs introduction_Old Kiwi|Lecture 13]]. ...an, E.M. Braverman, L.I. Rozoner. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Control, 1964, Vol.
    3 KB (366 words) - 07:48, 10 April 2008
  • Linear discriminant functions Old Kiwi
    Discriminant fuction that is a linear combination of the component x <br> ...wo-class problems; where teh ith problem is solvd by a linear discriminant function that separates points assigned to w_i from those not assigned to w_i<br>
    2 KB (433 words) - 22:11, 10 March 2008
  • Publications Old Kiwi
    ...f aspects of such problems: providing a better definition of the objective function, feature ...rom the Journal of Multivariate Analysis on Bayesian Estimators for Normal Discriminant Functions===
    39 KB (5,715 words) - 09:52, 25 April 2008
  • Lecture 4 - Bayes Classification Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,360 words) - 07:46, 17 January 2013
  • Linear Discriminant Functions Old Kiwi
    Discriminant fuction that is a linear combination of the component x <br> ...wo-class problems; where teh ith problem is solvd by a linear discriminant function that separates points assigned to w_i from those not assigned to w_i<br>
    2 KB (428 words) - 08:12, 7 April 2008
  • Fisher Linear Discriminant Old Kiwi
    Fisher's linear discriminant is a classification method that projects high-dimensional data onto a line ...vec{w}}^{T}{S}_{B}\vec{w}} {{\vec{w}}^{T}{S}_{W}\vec{w}}</math>, explicit function of <math>\vec{w}</math>
    3 KB (475 words) - 17:05, 28 March 2008
  • Lecture 19 - Nearest Neighbor Error Rates Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    5 KB (1,003 words) - 07:40, 17 January 2013
  • Lecture 20 - Density Estimation using Series Expansion and Decision Trees Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (1,047 words) - 07:42, 17 January 2013
  • Lecture 21 - Decision Trees(Continued) Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (1,012 words) - 07:42, 17 January 2013
  • Lecture 22 - Decision Trees and Clustering Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    6 KB (806 words) - 07:42, 17 January 2013
  • Naive Bayes Old Kiwi
    ...n with Gaussian class models will give the same results as Fisher's Linear Discriminant when the dimensions are independent. It may give results that are very clo function [data labels] = loadIris()
    3 KB (448 words) - 09:38, 22 April 2008
  • Lecture 23 - Spanning Trees Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    7 KB (1,060 words) - 07:43, 17 January 2013
  • Lecture 24 - Clustering and Hierarchical Clustering Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,254 words) - 07:43, 17 January 2013
  • Lecture 25 - Clustering Algorithms Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,259 words) - 07:43, 17 January 2013
  • Lecture 26 - Statistical Clustering Methods Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,244 words) - 07:44, 17 January 2013
  • Lecture 27 - Clustering by finding valleys of densities Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    8 KB (1,337 words) - 07:44, 17 January 2013
  • Lecture 28 - Final lecture Old Kiwi
    [[Lecture 5 - Discriminant Functions_Old Kiwi|5]], [[Lecture 6 - Discriminant Functions_Old Kiwi|6]],
    10 KB (1,728 words) - 07:55, 17 January 2013
  • Recommendations for nonlinear discrimination methods Old Kiwi
    #Try simple pattern recognition technique (K-nearest neighbor, linear discriminant analysis)first as a baseline before trying Neural network. #Use a radial basis function RBF (unsupervied selection of centers, weights optimized using a square err
    2 KB (311 words) - 09:49, 26 April 2008
  • Lecture 2 - Decision Hypersurfaces OldKiwi
    [[Lecture 5 - Discriminant Functions_OldKiwi|5]]| [[Lecture 6 - Discriminant Functions_OldKiwi|6]]|
    5 KB (744 words) - 10:17, 10 June 2013
  • ECE662:BoutinSpring08 OldKiwi
    * [[Lecture 5 - Discriminant Functions_OldKiwi|Lecture 5 - Discriminant Functions]] * [[Lecture 6 - Discriminant Functions_OldKiwi|Lecture 6 - Discriminant Functions]]
    7 KB (875 words) - 06:11, 13 February 2012
  • Lecture 9 - Linear Discriminant Functions OldKiwi
    [[Lecture 5 - Discriminant Functions_OldKiwi|5]]| [[Lecture 6 - Discriminant Functions_OldKiwi|6]]|
    9 KB (1,341 words) - 10:15, 10 June 2013
  • Lecture21ECE662S10
    ...linked to Fisher's linear discriminant. We then introduced Fisher's linear discriminant.
    961 B (135 words) - 07:27, 12 April 2010
  • Lecture24ECE662S10
    ...the existence of en underlying feature space extension for a given kernel function. ...eresting page]] on the use of [[Fisher_Linear_Discriminant|Fisher's linear discriminant]] when the data is not linearly separable.
    1 KB (188 words) - 09:36, 16 April 2010
  • Noteslecture20ECE662S10
    Thursday, April 8th 2010<br>(Continuation of the linear discriminant of [[Lecture19ECE662S10|lecture 19]])<br> ...in \mathcal{D} \right | \vec{c} \cdot \vec{y}_{1} \le 0</math> be the cost function. Hard to minimize !<br>
    8 KB (1,247 words) - 08:25, 11 May 2010
  • Decision Theory Glossary ECE662Spring2008
    Bayes' decision rule creates an objective function which minimizes the probability of error (misclassification). This method a Refers to the problem caused by exponential growth of hypervolume as a function of dimensionality. This term was coined by Richard Bellman in 1961.
    31 KB (4,787 words) - 17:21, 22 October 2010
  • Lecture2ECE662S12
    ...o our toy example to illustrate the concepts of "decision boundaries" and "discriminant functions". Our example only included one feature (hair length), so the cor ...t would be silly to attack such a problem by trying to find a discriminant function. It is much better to look up all the names (e.g., on the US social securit
    2 KB (358 words) - 11:30, 23 February 2012
  • Lecture3ECE662S12
    * finding a discriminant function (i.e., a real-valued function whose domain is the feature space); ...aic varieties, with an emphasis on hyperplanes (i.e. when the discriminant function is a degree one polynomial).
    2 KB (243 words) - 11:30, 23 February 2012
  • Lecture6ECE662S12
    ...(in the usual, Euclidean sense), the larger the value of the discriminant function <math>g_i(x)</math> for that class.
    2 KB (298 words) - 11:31, 23 February 2012
  • Lecture8ECE662S12
    ...then noticed the presence of the Mahalanobis distance in the discriminant function, and derived the relationship between the Mahalanobis distance and the Eucl
    3 KB (355 words) - 11:31, 23 February 2012
  • Lecture 1 - Introduction OldKiwi
    [[Lecture 5 - Discriminant Functions_OldKiwi|5]]| [[Lecture 6 - Discriminant Functions_OldKiwi|6]]|
    3 KB (413 words) - 10:17, 10 June 2013
  • Lecture 3 - Bayes classification OldKiwi
    [[Lecture 5 - Discriminant Functions_OldKiwi|5]]| [[Lecture 6 - Discriminant Functions_OldKiwi|6]]|
    6 KB (874 words) - 10:17, 10 June 2013

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