SP11 cs188 lecture 21 -- perceptron++ 6PP

SP11 cs188 lecture 21 -- perceptron++ 6PP - CS 188:...

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1 CS 188: Artificial Intelligence Spring 2011 Lecture 21: Perceptrons 4/13/2010 Pieter Abbeel – UC Berkeley Many slides adapted from Dan Klein. Announcements § Project 4: due Friday. § Final Contest: up and running! § Project 5 out! § Saturday, 10am-noon, 3 rd floor Sutardja Dai Hall Survey Outline § Generative vs. Discriminative § Perceptron Classification: Feature Vectors Hello, Do you want free printr cartriges? Why pay more when you can get them ABSOLUTELY FREE! Just # free : 2 YOUR_NAME : 0 MISSPELLED : 2 FROM_FRIEND : 0 ... SPAM or + PIXEL-7,12 : 1 PIXEL-7,13 : 0 ... NUM_LOOPS : 1 ... l 2 z Generative vs. Discriminative § Generative classifiers: § E.g. naïve Bayes § A causal model with evidence variables § Query model for causes given evidence § Discriminative classifiers: § No causal model, no Bayes rule, often no probabilities at all! § Try to predict the label Y directly from X § Robust, accurate with varied features § Loosely: mistake driven rather than model driven 6
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2 Some (Simplified) Biology § Very loose inspiration: human neurons 7 Linear Classifiers § Inputs are feature values § Each feature has a weight § Sum is the activation § If the activation is: § Positive, output +1 § Negative, output -1 Σ f 1 f 2 f 3 w 1 w 2 w 3 >0? 8
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SP11 cs188 lecture 21 -- perceptron++ 6PP - CS 188:...

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