PPT-Nearest Neighbors in High-Dimensional Data – The Emergenc

Milos Radovanovic Alexandros Nanopoulos Mirjana Ivanovic ICML 2009 Presented by Feng Chen Outline The Emergence of Hubs Skewness in Simulated Data Skewness in Real Data. Lowe Member IEEE Abstract For many computer vision and machine learning problems large training sets are key for good performance However the most computationally expensive part of many computer vision and machine learning algorithms consists of 642 Alimir. . Olivettr. . Artero. , Maria Cristina . Ferreiara. de Oliveira, . Haim. . levkowitz. Information Visualization 2004. Abstract. The idea is inspired by traditional image processing techniques such as grayscale manipulation.. LECTURE 10. Classification. . k-nearest neighbor classifier. . Naïve Bayes. . Logistic Regression. . Support Vector Machines. NEAREST NEIGHBOR CLASSIFICATION. Instance-Based Classifiers. Store the training records . Muhammad . Aamir. . Cheema. Outline. Introduction. Past Research. New Trends. Concluding Remarks. Definition. Services that integrate a user’s location with other information to provide added value to a user.. Lecturer: . Yishay. Mansour. Presentation: Adi Haviv and Guy Lev. 1. Lecture Overview. NN general overview. Various methods of NN. Models of the Nearest Neighbor . Algorithm. NN – Risk Analysis . KNN – . Nearest . Neighbor Method . for Pattern . Recognition. This lecture notes is based on the following paper:. B. . Tang and H. He, "ENN: Extended Nearest Neighbor Method for . Pattern Recognition. ," . by:. Peter Hirschmann. Diagnosing Methods. Monitor symptoms such as:. Resting Tremor. Bradykinesia. Rigidity. Postural Instability. Sub-symptom. Voice Problems. Use classification teaching algorithms to identify Parkinson’s. Peter Andras. School of Computing and Mathematics. Keele University. p.andras@keele.ac.uk. Overview. High-dimensional functions and low-dimensional manifolds. Manifold mapping. Function approximation over low-dimensional projections. 1982: -virus, 48,502 bp . 1995: h-influenzae, 1 Mbp . 2000: fly, 100 Mbp. 2001 – present. human (3Gbp), mouse (2.5Gbp), rat. *. , chicken, dog, chimpanzee, several fungal genomes. Gene Myers. Let’s sequence the human genome with the shotgun strategy. Nearest Neighbor Classification. Ashifur Rahman. About the Paper. Authors:. Trevor Hastie, . Stanford University. Robert . Tibshirani. , . University of Toronto. Publication:. KDD-1995. IEEE Transactions on Pattern Analysis and Machine Intelligence (1996). CSC 600: Data Mining. Class 16. Today…. Measures of . Similarity. Distance Measures. Nearest Neighbors. Similarity and Dissimilarity Measures. Used by a number of data mining techniques:. Nearest neighbors. Ilya . Razenshteyn. . (Microsoft Research Redmond). joint with. Alexandr. . Andoni. ,. Assaf . Naor. ,. Aleksandar . Nikolov. ,. Erik . Waingarten. How to measure distances?. Metric spaces. Normed spaces. Chapter 3 Lazy Learning – Classification Using Nearest Neighbors The approach An adage: if it smells like a duck and tastes like a duck, then you are probably eating duck. A maxim: birds of a feather flock together. CS771: Introduction to Machine Learning. Nisheeth. Improving . LwP. when classes are complex-shaped. 2. Using weighted Euclidean or . Mahalanobis. distance can sometimes help. Note: . Mahalanobis. distance also has the effect of rotating the axes which helps.