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

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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) ? ??? ???? ??? ?? ? ? ??? ??? ???? ??? ??? ??

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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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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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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

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Nearest Neighbor

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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., <sunny, normal, ..?> #neighbors = K (e.g., k=3) Often a parameter to be determined The form of the distance function

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Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI

Implementation of a Parallel K-Nearest Neighbor Algorithm Using MPI

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; 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