mining on car database employing learning and clustering algorithms
... of a particular feature of a class is not related to the presence (or absence) of the other entire feature. For example, a fruit may be considered to be an apple if it is red, round, and about 4" in diameter. Even if these features depend on each other or upon the existence of the other features, a ...
... of a particular feature of a class is not related to the presence (or absence) of the other entire feature. For example, a fruit may be considered to be an apple if it is red, round, and about 4" in diameter. Even if these features depend on each other or upon the existence of the other features, a ...
DOCX
... Additions – O(n) Multiplications by powers of two (actually left-shifts) – O(n) Four n/2-bit multiplications – xLyL, xLyR, xRyL, xRyR – with recursive calls. Our method for multiplying n-bit numbers starts by making recursive calls to multiply these four pairs of n/2-bit numbers (four sub-prob ...
... Additions – O(n) Multiplications by powers of two (actually left-shifts) – O(n) Four n/2-bit multiplications – xLyL, xLyR, xRyL, xRyR – with recursive calls. Our method for multiplying n-bit numbers starts by making recursive calls to multiply these four pairs of n/2-bit numbers (four sub-prob ...
M211 (ITC450 earlier)
... When developing software it is important to know how to solve problems in a computationally efficient way. Algorithms describe methods for solving problems under the constraints of the computers resources. Often the goal is to compute a solution as fast as possible, using as few resources as possibl ...
... When developing software it is important to know how to solve problems in a computationally efficient way. Algorithms describe methods for solving problems under the constraints of the computers resources. Often the goal is to compute a solution as fast as possible, using as few resources as possibl ...
File
... 1. Temperature readings are taken at 20 weather stations throughout the UK. Readings are taken at each station 8 times in one day. a) Describe how a 2-D array could be used to store the temperatures for each station. b) Declare this array c) Write an algorithm that will count the number of occasions ...
... 1. Temperature readings are taken at 20 weather stations throughout the UK. Readings are taken at each station 8 times in one day. a) Describe how a 2-D array could be used to store the temperatures for each station. b) Declare this array c) Write an algorithm that will count the number of occasions ...
lecture2-planning-p
... [Chow & Tsitsiklis ’89] C.S. Chow and J.N. Tsitsiklis: The complexity of dynamic programming, Journal of Complexity, 5:466—488, 1989. [Kearns et al. ’02] M.J. Kearns, Y. Mansour, A.Y. Ng: A sparse sampling algorithm for ...
... [Chow & Tsitsiklis ’89] C.S. Chow and J.N. Tsitsiklis: The complexity of dynamic programming, Journal of Complexity, 5:466—488, 1989. [Kearns et al. ’02] M.J. Kearns, Y. Mansour, A.Y. Ng: A sparse sampling algorithm for ...
Summary Team members: Weiqian Yan, Kanchan Khurad, and Yi
... The algorithm randomly selects parameters in each iteration and output the best cluster. While the theoretical run time of this algorithm is satisfactory, that is linear, but due to the large amount of data in high dimensional space problems, the algorithm is still very time consuming. Thus, the pap ...
... The algorithm randomly selects parameters in each iteration and output the best cluster. While the theoretical run time of this algorithm is satisfactory, that is linear, but due to the large amount of data in high dimensional space problems, the algorithm is still very time consuming. Thus, the pap ...
String-Matching Problem
... The Naive algorithm How would you do it? The Rabin-Karp algorithm Ingenious use of primes and number theory In practice optimal Literature Cormen, Leiserson, Rivest, “Introduction to Algorithms”, chapter 32, String Matching, The MIT Press, 2001, 906-932. Another algorithm: The Knuth-Morris-P ...
... The Naive algorithm How would you do it? The Rabin-Karp algorithm Ingenious use of primes and number theory In practice optimal Literature Cormen, Leiserson, Rivest, “Introduction to Algorithms”, chapter 32, String Matching, The MIT Press, 2001, 906-932. Another algorithm: The Knuth-Morris-P ...
PPT
... (hence 3 is a generator of Z*7) For a = 6, since 33 = 6, the output should be r = 3 Note: No efficient classical algorithm for DLP is known (and cryptosystems exist whose security is predicated on the computational difficulty of DLP) Efficient quantum algorithm for DLP? (Hint: it can be made to look ...
... (hence 3 is a generator of Z*7) For a = 6, since 33 = 6, the output should be r = 3 Note: No efficient classical algorithm for DLP is known (and cryptosystems exist whose security is predicated on the computational difficulty of DLP) Efficient quantum algorithm for DLP? (Hint: it can be made to look ...
FAST Lab Group Meeting 4/11/06
... • NMF maintains the interpretability of components of data like images or text or spectra (SDSS) • However as a low-D display it is not faithful in general to the original distances • Isometric NMF [Vasiloglou, Gray, Anderson, to be submitted SIAM DM 2008] preserves both distances and nonnegativity; ...
... • NMF maintains the interpretability of components of data like images or text or spectra (SDSS) • However as a low-D display it is not faithful in general to the original distances • Isometric NMF [Vasiloglou, Gray, Anderson, to be submitted SIAM DM 2008] preserves both distances and nonnegativity; ...
L10: k-Means Clustering
... • Enforces equal-sized clusters. Based on distance to cluster centers, not density. One adaptation that perhaps has better modeling is the EM formulation: Expectation-Maximization. It models each cluster as a Gaussian distribution Gi centered at ci . – For each point x ∈ X, find cluster ci with larg ...
... • Enforces equal-sized clusters. Based on distance to cluster centers, not density. One adaptation that perhaps has better modeling is the EM formulation: Expectation-Maximization. It models each cluster as a Gaussian distribution Gi centered at ci . – For each point x ∈ X, find cluster ci with larg ...
