l16_mahalanobis2

l16_mahalanobis2 - Final Project Questions Lets take up to...

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Final Project Questions • Let’s take up to an hour to – Review progress – Answer questions • Referencing sources in the term project – Direct quotes -- Place in quotes or indent and cite source in footnote or reference – Extensive paraphrase -- Cite source at beginning of chapter or section and explain degree to which it was used in a footnote – Common knowledge -- No reference req’d 16.881 MIT
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Mahalanobis Taguchi System Design of Systems which Rely on Accurate Classification = ? 16.881 MIT
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Outline • Review classification problems • Introduce the Mahalanobis distance • Demo on character recognition • Mahalanobis Taguchi System (MTS) • Case study on fire alarm system 16.881 MIT
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Classification Problems Many systems function by classifying instances into classes – Character recognition • Does R belong to A, B, C, ...? – Fire detection • Does this amount of smoke and heat indicate a fire or a BBQ ? – Air bag deployment Do these accelerometer inputs indicate a crash, a bumpy road, a hard stop ? http://www-engr.sjsu.edu/~knapp/HCIRODPR/PR_home.htm Pattern Recognition for HCI, Richard O. Duda 16.881 Department of Electrical Engineering, San Jose State University MIT
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Design Issues in Classifier Systems • What should be measured? • How should measurements be processed? • What is the criterion for demarcation? • What are the consequences of error? – Classified instance as A, but it isn’t A. – Classified instance as not A, but it is . 16.881 MIT
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Features Classification is made on the basis of measured features • Features should – Be easy (or inexpensive) to measure or extract – Clearly demarcate classes • Examples – Medical diagnosis – Character recognition DISPLAY( Clin) DISPLAY( Dlin) 16.881 MIT
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Feature Vectors Generally, there are several features required to make a classification • These features x i can be assembled into a vector Any object to be classified is represented by a point in n dimensional feature space x 1 x = x 2 x 3 x 1 x 2 x 3 x 16.881 MIT
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Joint Gaussian Distribution Density function entirely determined by mean vector
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