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This is where an iterative rule learning approach is followed and an EA is run several times in succession, with each run concentrating on evolving rule antecedents pertaining to a speci c class (eg, [116,290]) If a complete rule is encoded in an individual then the rule consequent may also be subject to evolution and change by the genetic operators A restriction may be placed on the crossover operator to ensure that only parents belonging to the same rule consequent are combined to produce offspring [371,407] With a Pittsburgh-style approach, generally, both rule antecedents and associated consequents are encoded The genetic operators may then act on the individual rules within a RB, or on the composition of the RB itself An alternative is proposed in [397], in which each individual represents a xed number of rule antecedents.

(offline mode: enter name=value pairs on standard input) num1=100 num2=200 Content-Type: text/html; charset=ISO-8859-1 100 + 200 = 100

Computer objects are not moved during a Movetree operation. You can use Netdom.exe, explained in the next section, to move computer objects between domains. Users personal data, logon scripts, policies, and so forth are not moved using Movetree. Local and Domain Global groups are not moved and all user accounts and groups maintain their security identities. ACLs are not reset. Universal groups are moved during a Movetree operation. The following objects cannot be moved: system objects, objects in the configuration or schema naming contexts, domain controllers, any object whose parent is a domain controller, any object with an identical name as an object in the new domain, and all objects in special containers (Builtin, ForeignSecurityPrincipal, System, and LostAndFound).

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This type of command-line debugging is very useful for small, less-complex scripts, but if you have a fairly large script, such as the formwizardpl, command-line debugging is too cumbersome In such a case, you need to use a combination of logging and debug printing Here is an example script, called calcpl, that uses logging and debug printing:

The consequents of the rules are dependent on the number of positive and negative examples they match in the training set and are determined prior to evaluation of the rule set 3242 Ant-Based Rule Induction FRANTIC (Fuzzy Rules from ANTInspired Computation) [108] implements a class-dependent iterative rule learning strategy, based on ant colony optimization More detail concerning ACO in general and its application to feature selection can be found in Section 102 For each class in the dataset one or more ACOs are run, and from each the best rule constructed is determined and added to the nal ruleset However, before the next ACO is run to nd another rule describing the same class, the cases belonging to that class that are covered by the previous best rule are removed.

!/usr/bin/perl -w use CGI qw(-debug); use constant DEBUG => 1; my $query = new CGI; my $num1 = $query->param( num1 ); my $num2 = $query->param( num2 ); print $query->header; if ($num1 == $num2) { # do something useful DEBUG and print STDERR num1 and num2 are same\n ; } elsif ($num1 > $num2 ) { # do something useful DEBUG and print STDERR num1 is greater than num2\n ; } elsif ($num1 < $num2 ) { # do something useful DEBUG and print STDERR num1 is less than num2\n ; } print print print print print $query->start_html( Calculator ); $query->h1( Calculator ); $query->p( Number 1: $num1 ); $query->p( Number 2: $num2 ); $query->end_html;

If a Movetree operation is paused or aborted, any objects that have not yet been moved but were targeted for the move are placed in an Orphan container found in the LostAndFound container. See 12 to learn more about the LostAndFound container.

exit 0;

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