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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI

Sep 14, 2014

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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI. Weston Monceaux March 20, 2003. Approach. Create Simple K-NN Parallelize Simple K-NN using MPI Benchmark both versions Try various Parallelization techniques Make implementation generic for reuse

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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI

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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI Weston Monceaux March 20, 2003
Approach • Create Simple K-NN • Parallelize Simple K-NN using MPI • Benchmark both versions • Try various Parallelization techniques • Make implementation generic for reuse • Try to keep all CPUs busy

K-nearest neighbor methods

K-nearest neighbor methods. William Cohen 10-601 April 2008. But first…. Onward: multivariate linear regression. col is feature. Multivariate. Univariate. row is example. Y. X. ACM Computing Surveys 2002. Review of K-NN methods (so far). Kernel regression.

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K-Nearest Neighbor Learning

K-Nearest Neighbor Learning. Dipanjan Chakraborty. Different Learning Methods. Eager Learning Explicit description of target function on the whole training set Instance-based Learning Learning=storing all training instances Classification=assigning target function to a new instance

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K nearest neighbor and Rocchio algorithm

K nearest neighbor and Rocchio algorithm. LING 572 Fei Xia 1/11/2007. Announcement. Hw2 is online now. It is due on Jan 20. Hw1 is due at 11pm on Jan 13 (Sat). Lab session after the class. Read DT Tutorial before next Tues’ class. K-Nearest Neighbor (kNN). Instance-based (IB) learning.

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K-Nearest Neighbor Mobile Recommendation System

2. ? ?. 1. ? ?. 2. ?? ??. 3. ????????? ??. 4. ???? ??. 5. ????? ??. 6. ?? ??. 7. ??. . . 8. ?????. 3. 1. ??. ??? ?? ????(nearest neighbor algorithm)?? ?? ?? ???? ???? ??? ? ??? ?? ?? ?? ???? ???? ??.NN ????? ?? ??? ???? ????(training set) ? ??? ???? ??? ?? ? ? ??? ??? ???? ??? ??? ??

570 views • 21 slides

Nearest Neighbor

Nearest Neighbor. Ling 572 Advanced Statistical Methods in NLP January 12, 2012. Roadmap. Instance-based learning Examples and Motivation Basic algorithm: k-Nearest Neighbors Issues: Selecting Weighting Voting Summary HW #2. Instance-based Learning. aka “Lazy Learning”

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K-nearest neighbor &amp; Naive Bayes

27-09-2012 Data mining. Sven Kouwenhoven Adam Swarek Chantal Choufoer. K-nearest neighbor &amp; Naive Bayes. General Plan. Part 1 Discuss K-nearest neighbor &amp; Naive Bayes 1 Method 2 Simple example 3 Real life example Part 2 Application of the method to the Charity Case

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A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm

A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm. kobe chai kobe@kobe.co.il. כריית מידע,המכללה האקדמית להנדסה ירושלים. Mountains. Multi-label learning. Trees. Lake. ? What is Multi-Label Objects. example: natural scene image.

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K Nearest Neighbor Classification Methods

K Nearest Neighbor Classification Methods. Qiang Yang. Training Set. Used for prediction/classification Given input x, (e.g., &lt;sunny, normal, ..?&gt; #neighbors = K (e.g., k=3) Often a parameter to be determined The form of the distance function

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Fast PNN-based Clustering Using K -nearest Neighbor Graph

Fast PNN-based Clustering Using K -nearest Neighbor Graph. Pasi Fränti, Olli Virmajoki and Ville Hautamäki 15.11.2003. UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE FINLAND. Agglomerative clustering. N = 22 ( data vectors ) M = 3 ( final clusters ). PNN method for clustering.

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Parallel Computing Using MPI

Parallel Computing Using MPI. Parallel Computing MPI CS Lab setup Simple MPI program MPI data type and user defined MPI data types. Parallel Computing. Traditional computing is sequential. Only one instruction can be executed at any given moment in time

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Query Dependent Ranking using K-Nearest Neighbor

Query Dependent Ranking using K-Nearest Neighbor. Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, Hang Li, Heung-Yeung Shum, Query Dependent Ranking with K Nearest Neighbor, Proc. of SIGIR 2008, 115-122. Introduction. Problem:

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Query Dependent Ranking Using K-Nearest Neighbor

Query Dependent Ranking Using K-Nearest Neighbor. SIGIR 2008 Presenter: Hsuan -Yu Lin. Outline. Introduction Motivation Method Experiments Conclusion. Introduction.

300 views • 16 slides

Fast PNN-based Clustering Using K -nearest Neighbor Graph

Fast PNN-based Clustering Using K -nearest Neighbor Graph. Pasi Fränti, Olli Virmajoki and Ville Hautamäki 15.11.2003. UNIVERSITY OF JOENSUU DEPARTMENT OF COMPUTER SCIENCE FINLAND. Content. Agglomerative clustering Graph-based PNN Creation of nearest neighbor graph Test results

479 views • 19 slides

Nearest Neighbor

Nearest Neighbor. Paul Hsiung March 16, 2004. Quick Review of NN. Set of points P Query point q Distance metric d Find p in P such that d(p,q) &lt; d(p’,q) for all p’ in P. p. q. NN Used In…. Image databases [Pentland et al ] Color indexing [swain et al ]

350 views • 18 slides

K Nearest Neighbor Classification Methods

K Nearest Neighbor Classification Methods. Qiang Yang. The K-Nearest Neighbor Method. Used for prediction/classification Given input x, (e.g., &lt;sunny, normal, ..?&gt; #neighbors = K (e.g., k=3) Often a parameter to be determined The form of the distance function

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K nearest neighbor

K nearest neighbor. LING 572 Fei Xia, Bill McNeill Week 2: 1/13/2009. Outline. Demo kNN Reading assignment #2. Demo. ML algorithms: Naïve Bayes, Decision stump, boosting, bagging, SVM, etc. Task: A binary classification problem with only two features.

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A k -Nearest Neighbor Based Algorithm for Multi-Label Classification

http://lamda.nju.edu.cn. A k -Nearest Neighbor Based Algorithm for Multi-Label Classification. Min-Ling Zhang zhangml@lamda.nju.edu.cn. Zhi-Hua Zhou zhouzh@nju.edu.cn. National Laboratory for Novel Software Technology Nanjing University, Nanjing, China July 26, 2005. Outline.

600 views • 19 slides

K Nearest Neighbor Classification Methods

K Nearest Neighbor Classification Methods. Training Set. Used for prediction/classification Given input x, (e.g., &lt;sunny, normal, ..?&gt; #neighbors = K (e.g., k=3) Often a parameter to be determined The form of the distance function K neighbors in training data to the input data x:

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K-Nearest Neighbor

K-Nearest Neighbor. Different Learning Methods. Eager Learning Explicit description of target function on the whole training set Instance-based Learning Learning=storing all training instances Classification=assigning target function to a new instance Referred to as “Lazy” learning.

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K-Nearest Neighbor Learning

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The K Nearest Neighbor Algorithm (kNN)

The K Nearest Neighbor Algorithm (kNN). Erik Zeitler Uppsala Database Laboratory. Examination. Examination is split in two parts Solve the assignment Oral examination During the oral examination The instructor validates your program using a script Non-working program

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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI

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Presentation Transcript

K-nearest neighbor methods

K-Nearest Neighbor Learning

K nearest neighbor and Rocchio algorithm

K-Nearest Neighbor Mobile Recommendation System

Nearest Neighbor

K-nearest neighbor &amp;amp; Naive Bayes

A k-Nearest Neighbor Based Multi-Instance Multi-Label Learning Algorithm

K Nearest Neighbor Classification Methods

Fast PNN-based Clustering Using K -nearest Neighbor Graph

Parallel Computing Using MPI

Query Dependent Ranking using K-Nearest Neighbor

Query Dependent Ranking Using K-Nearest Neighbor

Fast PNN-based Clustering Using K -nearest Neighbor Graph

Nearest Neighbor

K Nearest Neighbor Classification Methods

K nearest neighbor

A k -Nearest Neighbor Based Algorithm for Multi-Label Classification

K Nearest Neighbor Classification Methods

K-Nearest Neighbor

K-Nearest Neighbor Learning

The K Nearest Neighbor Algorithm (kNN)

K-nearest neighbor & Naive Bayes