'Dimensional input space' presentation slideshows

Last lecture summary

Last lecture summary. Information theory. quantifies information, information is inherently linked with uncertainty and surprise. Consider a random variable and ask how much information is received when a specific value for this variable is observed.

714 views • 64 slides

Support Vector Machines: Classification Algorithms and Applications

796 views • 52 slides

Text Categorization With Support Vector Machines: Learning With Many Relevant Features

Text Categorization With Support Vector Machines: Learning With Many Relevant Features. By Thornsten Joachims Presented By Meghneel Gore. Goal of Text Categorization. Classify documents into a number of pre-defined categories. Documents can be in multiple categories

537 views • 24 slides

Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini

NETTAB 2004 Workshop on Models and M etaphors from Biology to Bioinformatics Tools. Random subspace ensembles for the bio-molecular diagnosis of tumors. Alberto Bertoni, Raffaella Folgieri, Giorgio Valentini. {bertoni,folgieri,valentini}@dsi.unimi.it. Outline.

403 views • 20 slides

Supervised Function Approximation

Supervised Function Approximation. In supervised learning, we train an ANN with a set of vector pairs, so-called exemplars . Each pair ( x , y ) consists of an input vector x and a corresponding output vector y .

320 views • 17 slides

Introduction to Matlab and Simulink

Introduction to Matlab and Simulink. Dr Martin Brown E1k, Control Systems Centre School of Electrical and Electronic Engineering University of Manchester Tel: 0161 306 4672 martin.brown@manchester.ac.uk EEE Intranet. Background and Aims.

513 views • 14 slides