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probability of encountering the specific instance X I , as well as the probability of the observed target value diShow that Equation (65) holds even under this more general setting Hint: Consider the analysis of Section 65 65 Consider the Minimum Description Length principle applied to the hypothesis space H consisting of conjunctions of up to n boolean attributes (eg, Sunny A Warm) Assume each hypothesis is encoded simply by listing the attributes present in the hypothesis, where the number of bits needed to encode any one of the n boolean attributes is log, n Suppose the encoding of an example given the hypothesis uses zero bits if the example is consistent with the hypothesis and uses log, m bits otherwise (to indicate which of the m examples was misclassified-the correct classification can be inferred to be the opposite of that predicted by the hypothesis) ( a ) Write down the expression for the quantity to be minimized according to the Minimum Description Length principle ( b ) Is it possible to construct a set of training data such that a consistent hypothesis exists, but MDL chooses a less consistent hypothesis If so, give such a training set If not, explain why not ( c ) Give probability distributions for P ( h ) and P(D1h) such that the above MDL algorithm outputs MAP hypotheses 66 Draw the Bayesian belief network that represents the conditional independence assumptions of the naive Bayes classifier for the PlayTennis problem of Section 691 Give the conditional probability table associated with the node Wind

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#import <UIKit/UIKith> @interface ButtonsBackgroundViewController : UIViewController { IBOutlet UIButton * clearButton; IBOutlet UIButton * smallButton; } @property (nonatomic, retain) IBOutlet UIButton * clearButton; @property (nonatomic, retain) IBOutlet UIButton * smallButton; - (IBAction) disableBut: (id) sender; @end

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Buntine W L (1994) Operations for learning with graphical models Journal of Art$cial Intelligence Research, 2, 159-225 http://wwwcswashingtonedu/research/jair/homhtml Casella, G, & Berger, R L (1990) Statistical inference Pacific Grove, CA: Wadsworth & Brooks/Cole Cestnik, B (1990) Estimating probabilities: A crucial task in machine learning Proceedings of the Ninth European Conference on Am&5al Intelligence (pp 147-149) London: Pitman Chauvin, Y, & Rumelhart, D (1995) Backpropagation: Theory, architectures, and applications, (edited collection) Hillsdale, NJ: Lawrence Erlbaum Assoc A Cheeseman, P, Kelly, J, Self, M, Stutz, J, Taylor, W, & Freeman, D (1988) AUTOCLASS: bayesian classification system Proceedings of AAAI I988 (pp 607-611) Cooper, G (1990) Computational complexity of probabilistic inference using Bayesian belief networks (research note) Art@cial Intelligence, 42, 393-405 Cooper, G, & Herskovits, E (1992) A Bayesian method for the induction of probabilistic networks from data Machine Learning, 9, 309-347 Dagum, P, & Luby, M (1993) Approximating probabilistic reasoning in Bayesian belief networks is NP-hard Art$cial Intelligence, 60(1), 141-153 Dempster, A P, Laird, N M, & Rubin, D B (1977) Maximum likelihood from incomplete data via the EM algorithm Journal of the Royal Statistical Society, Series B, 39(1), 1-38 Domingos, P, & Pazzani, M (1996) Beyond independence: Conditions for the optimality of the simple Bayesian classifier Proceedings of the 13th International Conference on Machine Learning @p 105-112) Duda, R O, & Hart, P E (1973) Pattern class$cation and scene analysis New York: John Wiley & Sons Hearst, M, & Hirsh, H (Eds) (1996) Papers from the AAAI Spring Symposium on Machine Learning in Information Access, Stanford, March 25-27 http://wwwparcxeroxcom/ist~ projects/mlia/

This means that the width of the movie shape has been matched to the width of the TV shape, leaving a gap at the top and the bottom This is called letterboxing It does not refer to postal pugilism but rather to the process of putting the movie in a black box with a hole the shape of a standard paper envelope The black bars are called mattes At other times you might see the words This presentation has been formatted for television at the beginning of a movie This indicates that a pan and scan process has been used, where a TV-shaped window over the film image is moved from side to side or up and down or is zoomed in and out (Figures 314 and 315) This process is more complicated than just chopping off a little from each side; sometimes the important part of the picture is all on one side or mostly on the other side, and sometimes there is more picture on the film above or below what is shown in the theater, so the artist who transfers the movie to video must determine for every scene how much of each side should be chopped off or how much additional picture from above or below should be included in order to preserve the action and story line For the past 20 years or so, most films have been shot flat, sometimes called soft matte The cinematographer has two rectangles in the viewfinder, one for 185 (or wider) and one for 4:3 (see Figure 313) He or she composes the shots to look good in the 185 rectangle while making sure that no crew, equipment, or raw set edges are visible above or below in the 4:3 area For presentation in the theater, a theatrical matte is used to mask off the top and bottom either when the film is printed or with an aperture.

#import "ButtonsBackgroundViewControllerh" @implementation ButtonsBackgroundViewController @synthesize clearButton; @synthesize smallButton; - (IBAction) disableBut: (id) sender { if(clearButtonenabled == YES) { clearButtonenabled = NO; smallButtonenabled = NO; [((UIButton *) sender) setTitle:@"Enable" forState: UIControlStateNormal]; } else { clearButtonenabled = YES; smallButtonenabled = YES; [((UIButton *) sender) setTitle:@"Disable" forState: UIControlStateNormal]; } } - (void)dealloc { [clearButton release]; [smallButton release]; [super dealloc]; } @end

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