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- 23:43, 24 April 2008 (diff | hist) . . (+626) . . ECE662:ChangeLog Old Kiwi (→The ChangeLog)
- 23:43, 24 April 2008 (diff | hist) . . (+610) . . ECE662:ChangeLog OldKiwi (→The ChangeLog)
- 23:38, 24 April 2008 (diff | hist) . . (+999) . . N KNN-K Nearest Neighbor Old Kiwi (New page: The classifiers do not use any model to fit the data and only based on memory. The KNN uses neighborhood classification as the predication value of the new query. It has advantages - nonpa...)
- 23:38, 24 April 2008 (diff | hist) . . (+999) . . N KNN-K Nearest Neighbor OldKiwi (New page: The classifiers do not use any model to fit the data and only based on memory. The KNN uses neighborhood classification as the predication value of the new query. It has advantages - nonpa...)
- 23:37, 24 April 2008 (diff | hist) . . (+10) . . ECE662:Glossary Old Kiwi (→Bayesian Parameter Estimation)
- 23:37, 24 April 2008 (diff | hist) . . (+9) . . ECE662:Glossary OldKiwi (→Bayesian Parameter Estimation) (current)
- 23:34, 24 April 2008 (diff | hist) . . (+247) . . N Euclidean Distance (ED) Old Kiwi (New page: Is the distance between two points in a cartesian coordinate system that is "measured by a ruler". The Euclidean distance between the points X=[x1,x2,...xn] and Y=[y1,y2,...yn] is defined ...)
- 23:34, 24 April 2008 (diff | hist) . . (+247) . . N Euclidean Distance (ED) OldKiwi (New page: Is the distance between two points in a cartesian coordinate system that is "measured by a ruler". The Euclidean distance between the points X=[x1,x2,...xn] and Y=[y1,y2,...yn] is defined ...) (current)
- 23:34, 24 April 2008 (diff | hist) . . (-2) . . ECE662:Glossary OldKiwi (→Euclidean Distance (ED))
- 23:34, 24 April 2008 (diff | hist) . . (-2) . . ECE662:Glossary Old Kiwi (→Euclidean Distance (ED))
- 23:33, 24 April 2008 (diff | hist) . . (+85) . . N Generalized Rayleigh Quotient Old Kiwi (New page: <math>J(\vec{w}) = \frac{\vec{w}^{\top}S_B \vec{w}}{\vec{w}^{\top}S_w \vec{w}}</math>) (current)
- 23:33, 24 April 2008 (diff | hist) . . (+85) . . N Generalized Rayleigh Quotient OldKiwi (New page: <math>J(\vec{w}) = \frac{\vec{w}^{\top}S_B \vec{w}}{\vec{w}^{\top}S_w \vec{w}}</math>) (current)
- 23:32, 24 April 2008 (diff | hist) . . (+35) . . N Taxicab Distance Old Kiwi (New page: see Manhattan Distance) (current)
- 23:32, 24 April 2008 (diff | hist) . . (+34) . . N Taxicab Distance OldKiwi (New page: see Manhattan Distance) (current)
- 23:30, 24 April 2008 (diff | hist) . . (0) . . Unsupervised learning Old Kiwi (current)
- 23:30, 24 April 2008 (diff | hist) . . (0) . . Unsupervised learning OldKiwi (current)
- 23:29, 24 April 2008 (diff | hist) . . (+13) . . ECE662:Glossary Old Kiwi (→Supervised learning)
- 23:29, 24 April 2008 (diff | hist) . . (+12) . . ECE662:Glossary OldKiwi (→Supervised learning)
- 23:29, 24 April 2008 (diff | hist) . . (+250) . . N Uninformative Prior Old Kiwi (New page: An uninformative prior gives very little, a more vague or a general information about the variable. It is important to realize that the term uninformative does not mean no information. (Se...) (current)
- 23:29, 24 April 2008 (diff | hist) . . (+248) . . N Uninformative Prior OldKiwi (New page: An uninformative prior gives very little, a more vague or a general information about the variable. It is important to realize that the term uninformative does not mean no information. (Se...) (current)
- 23:28, 24 April 2008 (diff | hist) . . (+180) . . N Unsupervised learning Old Kiwi (New page: The goal of the machine is to build a model of x that can be used for reasoning, decision making, predicting things, communicating etc. (See also: Supervised Learning))
- 23:28, 24 April 2008 (diff | hist) . . (+179) . . N Unsupervised learning OldKiwi (New page: The goal of the machine is to build a model of x that can be used for reasoning, decision making, predicting things, communicating etc. (See also: Supervised Learning))
- 23:27, 24 April 2008 (diff | hist) . . (+145) . . N Training Old Kiwi (New page: When we present a pattern recognition with a set of classified patterns so that it can learn the characteristics of the set, we call it training.) (current)
- 23:27, 24 April 2008 (diff | hist) . . (+145) . . N Training OldKiwi (New page: When we present a pattern recognition with a set of classified patterns so that it can learn the characteristics of the set, we call it training.) (current)
- 23:27, 24 April 2008 (diff | hist) . . (+137) . . N Unbiased Estimator Old Kiwi (New page: An estimator is said to be unbiased if and only if the expected value (average) of its estimate is the true value of the thing estimated.) (current)
- 23:27, 24 April 2008 (diff | hist) . . (+137) . . N Unbiased Estimator OldKiwi (New page: An estimator is said to be unbiased if and only if the expected value (average) of its estimate is the true value of the thing estimated.) (current)
- 23:25, 24 April 2008 (diff | hist) . . (+117) . . N Testing Old Kiwi (New page: When we present a trained recognition system with an unknown pattern and ask it to classify it, we call that testing.) (current)
- 23:25, 24 April 2008 (diff | hist) . . (+117) . . N Testing OldKiwi (New page: When we present a trained recognition system with an unknown pattern and ask it to classify it, we call that testing.) (current)
- 23:25, 24 April 2008 (diff | hist) . . (+474) . . N Slack Variable Old Kiwi (New page: In linear programming , a slack variable is referred to as an additional variable that has been introduced to the optimization problem to turn a inequality constraint into an equality cons...) (current)
- 23:25, 24 April 2008 (diff | hist) . . (+474) . . N Slack Variable OldKiwi (New page: In linear programming , a slack variable is referred to as an additional variable that has been introduced to the optimization problem to turn a inequality constraint into an equality cons...) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+113) . . N Reinforcement learning Old Kiwi (New page: A reinforcement learning machine learns to perform actions which will maximize rewards (or minimize punishments).) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+113) . . N Reinforcement learning OldKiwi (New page: A reinforcement learning machine learns to perform actions which will maximize rewards (or minimize punishments).) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+232) . . N Quadratic Programming Problem Old Kiwi (New page: A linearly constrained optimization problem with a quadratic objective function is called a quadratic program (QP). Quadratic programming is often considered as a discipline in and of itse...) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+232) . . N Quadratic Programming Problem OldKiwi (New page: A linearly constrained optimization problem with a quadratic objective function is called a quadratic program (QP). Quadratic programming is often considered as a discipline in and of itse...) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+562) . . N Pruning Old Kiwi (New page: Pruning (also called as inverse splitting) is a term in mathematics and informatics which allows to cut parts of a decision tree. Pruning is done by taking two leaves that have a common pa...) (current)
- 23:24, 24 April 2008 (diff | hist) . . (+562) . . N Pruning OldKiwi (New page: Pruning (also called as inverse splitting) is a term in mathematics and informatics which allows to cut parts of a decision tree. Pruning is done by taking two leaves that have a common pa...) (current)
- 23:20, 24 April 2008 (diff | hist) . . (+106) . . N Prior Old Kiwi (New page: The probability that adjusts the classification of cases by using known information, hence the name prior.) (current)
- 23:20, 24 April 2008 (diff | hist) . . (+106) . . N Prior OldKiwi (New page: The probability that adjusts the classification of cases by using known information, hence the name prior.) (current)
- 23:19, 24 April 2008 (diff | hist) . . (-47) . . Partial Differential Equations (PDE) Old Kiwi (current)
- 23:19, 24 April 2008 (diff | hist) . . (-46) . . Partial Differential Equations (PDE) OldKiwi (current)
- 23:19, 24 April 2008 (diff | hist) . . (-47) . . ECE662:Glossary Old Kiwi (→Partial Differential Equations (PDE))
- 23:19, 24 April 2008 (diff | hist) . . (-46) . . ECE662:Glossary OldKiwi (→Partial Differential Equations (PDE))
- 23:18, 24 April 2008 (diff | hist) . . (+13) . . ECE662:Glossary Old Kiwi (→Partial Differential Equations (PDE))
- 23:18, 24 April 2008 (diff | hist) . . (+12) . . ECE662:Glossary OldKiwi (→Partial Differential Equations (PDE))
- 23:17, 24 April 2008 (diff | hist) . . (+236) . . N Partial Differential Equations (PDE) Old Kiwi (New page: PDE's are differentiable equations of several independent variables in which can be differentiated with respect to those variables. In this course PDE's are used to find cluster boundaries...)
- 23:17, 24 April 2008 (diff | hist) . . (+235) . . N Partial Differential Equations (PDE) OldKiwi (New page: PDE's are differentiable equations of several independent variables in which can be differentiated with respect to those variables. In this course PDE's are used to find cluster boundaries...)
- 01:55, 17 April 2008 (diff | hist) . . (+708) . . N Likelihood Principle Old Kiwi (New page: The likelihood principle is a principle of statistical inference which asserts that all of the information in a sample is contained in the likelihood function. A likelihood function arises...) (current)
- 01:55, 17 April 2008 (diff | hist) . . (+708) . . N Likelihood Principle OldKiwi (New page: The likelihood principle is a principle of statistical inference which asserts that all of the information in a sample is contained in the likelihood function. A likelihood function arises...) (current)
- 01:54, 17 April 2008 (diff | hist) . . (+3) . . ECE662:Glossary Old Kiwi (→Parzen Window)
- 01:54, 17 April 2008 (diff | hist) . . (+3) . . ECE662:Glossary OldKiwi (→Parzen Window)
- 01:54, 17 April 2008 (diff | hist) . . (+1,182) . . N Parzen Window Old Kiwi (New page: Parzen windows are very similar to K nearest neighborhoods(KNN). Both methods can generate very complex decision boundaries. The main difference is that instead of looking at the k closest...) (current)
- 01:54, 17 April 2008 (diff | hist) . . (+1,182) . . N Parzen Window OldKiwi (New page: Parzen windows are very similar to K nearest neighborhoods(KNN). Both methods can generate very complex decision boundaries. The main difference is that instead of looking at the k closest...) (current)
- 01:51, 17 April 2008 (diff | hist) . . (+1) . . ECE662:Glossary Old Kiwi
- 01:51, 17 April 2008 (diff | hist) . . (+1) . . ECE662:Glossary OldKiwi
- 01:50, 17 April 2008 (diff | hist) . . (+594) . . ECE662:ChangeLog Old Kiwi (→The ChangeLog)
- 01:50, 17 April 2008 (diff | hist) . . (+578) . . ECE662:ChangeLog OldKiwi (→The ChangeLog)
- 01:45, 17 April 2008 (diff | hist) . . (+657) . . N Principal Component Analysis Old Kiwi (New page: Constructing new features which are the principal components of a data set. The principal components are random variables of maximal variance constructed from linear combinations of the in...) (current)
- 01:45, 17 April 2008 (diff | hist) . . (+657) . . N Principal Component Analysis OldKiwi (New page: Constructing new features which are the principal components of a data set. The principal components are random variables of maximal variance constructed from linear combinations of the in...) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+71) . . N Posterior Old Kiwi (New page: The probability, using prior knowledge, that a case belongs to a group.) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+71) . . N Posterior OldKiwi (New page: The probability, using prior knowledge, that a case belongs to a group.) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+577) . . N Penalty Methods Old Kiwi (New page: In optimization, penalty methods are used to reformulate a constraint optimization problem into several unconstrained optimization problems. It can be shown that the solutions of these der...) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+577) . . N Penalty Methods OldKiwi (New page: In optimization, penalty methods are used to reformulate a constraint optimization problem into several unconstrained optimization problems. It can be shown that the solutions of these der...) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+1,179) . . N Pazen Window Old Kiwi (New page: Parzen windows are very similar to K nearest neighborhoods(KNN). Both methods can generate very complex decision boundaries. The main difference is that instead of looking at the k closest...) (current)
- 01:44, 17 April 2008 (diff | hist) . . (+1,179) . . N Pazen Window OldKiwi (New page: Parzen windows are very similar to K nearest neighborhoods(KNN). Both methods can generate very complex decision boundaries. The main difference is that instead of looking at the k closest...) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+71) . . N Patterns Old Kiwi (New page: The items that we are trying to classify are vectors of these features.) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+71) . . N Patterns OldKiwi (New page: The items that we are trying to classify are vectors of these features.) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+165) . . N Parametric Classifiers Old Kiwi (New page: We find parametric decision boundaries to approximate true decision boundaries between classes. (Discussed in Lecture 9 - Linear Discriminant Functions)) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+164) . . N Parametric Classifiers OldKiwi (New page: We find parametric decision boundaries to approximate true decision boundaries between classes. (Discussed in Lecture 9 - Linear Discriminant Functions)) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+343) . . N Parametric Model Old Kiwi (New page: A parametric model is a set of related mathematical equations in which alternative scenarios are defined by changing the assumed values of a set of fixed coefficients (parameters). In stat...) (current)
- 01:43, 17 April 2008 (diff | hist) . . (+343) . . N Parametric Model OldKiwi (New page: A parametric model is a set of related mathematical equations in which alternative scenarios are defined by changing the assumed values of a set of fixed coefficients (parameters). In stat...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+197) . . N Parameter Estimation Old Kiwi (New page: Density estimation when the density is assumed to be in a specific parametric family. Special cases include maximum likelihood, maximum a posteriori, unbiased estimation, and predictive es...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+197) . . N Parameter Estimation OldKiwi (New page: Density estimation when the density is assumed to be in a specific parametric family. Special cases include maximum likelihood, maximum a posteriori, unbiased estimation, and predictive es...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+637) . . N Overfitting Old Kiwi (New page: In statistics, overfitting means that some of the relationships that appear statistically significant are actually just noise. A model with overfitting has much more freedom degrees than t...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+637) . . N Overfitting OldKiwi (New page: In statistics, overfitting means that some of the relationships that appear statistically significant are actually just noise. A model with overfitting has much more freedom degrees than t...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+319) . . N Non-parametric Model Old Kiwi (New page: Non-parametric models differ from parametric models in that the model structure is not specified a priori but is instead determined from data. The term nonparametric is not meant to imply ...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+319) . . N Non-parametric Model OldKiwi (New page: Non-parametric models differ from parametric models in that the model structure is not specified a priori but is instead determined from data. The term nonparametric is not meant to imply ...) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+185) . . N Nonparametric regression/density estimation Old Kiwi (New page: An approach to regression/density estimation that doesn't require much prior knowledge but only a large amount of data. This includes histograms, kernel smoothing, and nearest-neighbor.) (current)
- 01:42, 17 April 2008 (diff | hist) . . (+185) . . N Nonparametric regression/density estimation OldKiwi (New page: An approach to regression/density estimation that doesn't require much prior knowledge but only a large amount of data. This includes histograms, kernel smoothing, and nearest-neighbor.) (current)
- 01:41, 17 April 2008 (diff | hist) . . (+398) . . N Minkowski Metric Old Kiwi (New page: The k-Minkowski metric between two points <math>P_1 = (x_1,x_2,...,x_n)</math> and <math>P_2 = (y_1,y_2,...,y_n)</math> is defined as <math> d_k = (\sum_{i=1}^n \parallel x_i-y_i \parallel...) (current)
- 01:41, 17 April 2008 (diff | hist) . . (+398) . . N Minkowski Metric OldKiwi (New page: The k-Minkowski metric between two points <math>P_1 = (x_1,x_2,...,x_n)</math> and <math>P_2 = (y_1,y_2,...,y_n)</math> is defined as <math> d_k = (\sum_{i=1}^n \parallel x_i-y_i \parallel...) (current)
- 01:41, 17 April 2008 (diff | hist) . . (+33) . . N MLE Old Kiwi (New page: See Maximum Likelihood Estimation) (current)
- 01:41, 17 April 2008 (diff | hist) . . (+33) . . N MLE OldKiwi (New page: See Maximum Likelihood Estimation) (current)
- 01:40, 17 April 2008 (diff | hist) . . (+257) . . N Manhattan Distance Old Kiwi (New page: Also known as taxicab metric. The Manhattan distance between two points (X,Y) in a cartesian system is defined as <math>dist(X,Y)=\sum_{i=1}^n{|x_i-y_i|}</math>. This is equal to the lengt...) (current)
- 01:40, 17 April 2008 (diff | hist) . . (+257) . . N Manhattan Distance OldKiwi (New page: Also known as taxicab metric. The Manhattan distance between two points (X,Y) in a cartesian system is defined as <math>dist(X,Y)=\sum_{i=1}^n{|x_i-y_i|}</math>. This is equal to the lengt...) (current)
- 01:40, 17 April 2008 (diff | hist) . . (+340) . . N Linear Discriminant Functions (LDF) Old Kiwi (New page: Functions that are linear combinations of x. <math>g(x) = w^t x + w_0 </math> Where <math>w</math> is the weight vector and <math>w_0</math> is the bias as threshold. In the two category ...) (current)
- 01:40, 17 April 2008 (diff | hist) . . (+340) . . N Linear Discriminant Functions (LDF) OldKiwi (New page: Functions that are linear combinations of x. <math>g(x) = w^t x + w_0 </math> Where <math>w</math> is the weight vector and <math>w_0</math> is the bias as threshold. In the two category ...) (current)
- 10:23, 7 April 2008 (diff | hist) . . (+405) . . ECE662:ChangeLog Old Kiwi (→The ChangeLog)
- 10:23, 7 April 2008 (diff | hist) . . (+394) . . ECE662:ChangeLog OldKiwi (→The ChangeLog)
- 10:19, 7 April 2008 (diff | hist) . . (+233) . . N LUT - Look-Up Table Old Kiwi (New page: In classification applications, LUT's can be used for comparing decisions, as long as memory is available. This method requires a discrete feature space that is reasonably small. (This met...) (current)
- 10:19, 7 April 2008 (diff | hist) . . (+233) . . N LUT - Look-Up Table OldKiwi (New page: In classification applications, LUT's can be used for comparing decisions, as long as memory is available. This method requires a discrete feature space that is reasonably small. (This met...) (current)
- 10:19, 7 April 2008 (diff | hist) . . (+448) . . N Lagrange Multipliers Old Kiwi (New page: In mathematical optimization problems, the method of Lagrange multipliers, named after Joseph Louis Lagrange, is a method for finding the extrema of a function of several variables subject...) (current)
- 10:19, 7 April 2008 (diff | hist) . . (+448) . . N Lagrange Multipliers OldKiwi (New page: In mathematical optimization problems, the method of Lagrange multipliers, named after Joseph Louis Lagrange, is a method for finding the extrema of a function of several variables subject...) (current)
- 10:18, 7 April 2008 (diff | hist) . . (+413) . . N Kernel Functions Old Kiwi (New page: These functions operate in the feature space without ever computing the coordinates of the data in that space, but rather by simply computing the inner products between the mappings of all...) (current)
- 10:18, 7 April 2008 (diff | hist) . . (+413) . . N Kernel Functions OldKiwi (New page: These functions operate in the feature space without ever computing the coordinates of the data in that space, but rather by simply computing the inner products between the mappings of all...) (current)
- 10:18, 7 April 2008 (diff | hist) . . (+321) . . N Informative Prior Old Kiwi (New page: In the Bayesian framework, the prior distribution of the variable is called an informative prior if it provide some specific information about the variable. Informative priors allows to in...) (current)
- 10:18, 7 April 2008 (diff | hist) . . (+321) . . N Informative Prior OldKiwi (New page: In the Bayesian framework, the prior distribution of the variable is called an informative prior if it provide some specific information about the variable. Informative priors allows to in...) (current)
- 10:17, 7 April 2008 (diff | hist) . . (+248) . . N Impurity Old Kiwi (New page: Impurity of a class is defined as the amount of data misclassified into that class. It is zero when all training data belongs to one class. See Lecture 21 - Decision Trees(Continued) f...) (current)
- 10:17, 7 April 2008 (diff | hist) . . (+247) . . N Impurity OldKiwi (New page: Impurity of a class is defined as the amount of data misclassified into that class. It is zero when all training data belongs to one class. See Lecture 21 - Decision Trees(Continued) f...) (current)
- 10:16, 7 April 2008 (diff | hist) . . (+503) . . N Histogram Density Estimation OldKiwi (New page: Histogram Density Estimation is one of the primitive and easiest non-parametric density estimation methods. The given feature space is divided into equally-spaced bins or cells. The number...) (current)
- 10:16, 7 April 2008 (diff | hist) . . (+503) . . N Histogram Density Estimation Old Kiwi (New page: Histogram Density Estimation is one of the primitive and easiest non-parametric density estimation methods. The given feature space is divided into equally-spaced bins or cells. The number...) (current)
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