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The FIND-Salgorithm illustrates one way in which the more-generaldhan partial ordering can be used to organize the search for an acceptable hypothesis The search moves from hypothesis to hypothesis, searching from the most specific to progressively more general hypotheses along one chain of the partial ordering Figure 22 illustrates this search in terms of the instance and hypothesis spaces At each step, the hypothesis is generalized only as far as necessary to cover the new positive example Therefore, at each stage the hypothesis is the most specific hypothesis consistent with the training examples observed up to this point (hence the name FIND-S)The literature on concept learning is

3; one");

MPEG-2 MP@ML/SP@ML VBR/CBR or MPEG-1 VBR/CBR 24 fpsa (film), 2997 fpsb (525/60), 25 fpsb (625/50) 2997 fpsb (525/60), 25 fpsb (625/50) 720 720 352 480, 704 576, 704 480, 352 576, 352 480 (525/60); 576 (625/50) 288 (625/50)

Loops should prove familiar if you know Java, as should the do-while loop and the for loop (Listing 2-9) Listing 2-9 The while, do-while, and for loops using C

240 (525/60); 352

+ X3 = <Rainy Cold High Strong Warm Change>, x - <Sunny Warm High Strong Cool Change>, + 4x2 = <Sunny Warm High Strong Warm Same>,

int i = 0; while(i < 20) { printf("loop%d", i); i++; } do { printf("loop%d", i); i--; } while(i > 0) for(int i =0; i < 20; i++) { printf("loop%d", i); }

36 fields (525/60), 30 fields (625/50) 18 frames (525/60), 15 frames (625/50) 4:3 or 16:9 anamorphic c Refer to Table 617

where c is the number of distinct values the target function may take on, and where pi is the proportion of examples from S for which the target function takes on the ith value This entropy measure, combined with a test for statistical significance, is used in the CN2 algorithm of Clark and Niblett (1989) It is also the basis for the information gain measure used by many decision tree learning algorithms

The UIImagePickerController is different from other view controllers Rather than developers creating the controller s view and adding components to the view s canvas, the UIImage PickerController s views are already created and are part of the UIKit library Developers simply determine the controller s source type and implement a delegate for the controller The controller creates and manages the views while the delegate responds to the view being dismissed by a user

Progressive (decoder performs 3-2 or 2-2 pulldown)

The iPod touch, as of this book s publication, does not have a camera The iPhone Simulator also lacks a camera If you attempted to use an iPod touch s nonexistent camera, you would obtain an exception Attempting to use the camera on an iPhone Simulator results in a nonresponsive application after it logs a message to the debugger console (Figure 13-15)

(ie, variable-free) rules In this section, we consider learning rules that contain variables-in particular, learning first-order Horn theories Our motivation for considering such rules is that they are much more expressive than propositional rules Inductive learning of first-order rules or theories is often referred to as inductive logic programming (or L P for short), because this process can be viewed as automatically inferring PROLOG programs from examples PROLOG is a general purpose, Turing-equivalent programming language in which programs are expressed as collections of Horn clauses

Interlaced (5994 fields per second or 50 fields per second)

To avoid an exception or nonresponsive application, the UIImagePickerController provides the isSourceTypeAvailable: method

Video Stream DVD-Video is based on a subset of MPEG-2 (ISO/IEC 13818) Main Profile at Main Level (MP@ML) or Simple Profile at Main Level (SP@ML) Constant and variable bit rates (CBR and VBR) are supported DVD adds additional restrictions, which are detailed in Table 620 DVDVideo also supports MPEG-1 video at constant and variable bit rates (see Table 620) Before MPEG-2 compression occurs, the video is subsampled from ITUR BT601 format at 4:2:0 sampling with 8 bits of precision, which allocates an average of 12 bits per pixel The actual color depth of the samples is 24 bits (1 byte for Y, 1 byte for Cb, and 1 byte for Cr), but the C samples are shared by 4 pixels The uncompressed source data rate is 124416 Mbps (720 480 12 30 or 720 576 12 25) For 24-fps film, the source is typically at video frame rates of 30 fps (a telecine pulldown process has added duplicate fields) The MPEG encoder performs an inverse telecine process to remove