Algorithm-Classifier-IsolationForest
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lib/Algorithm/Classifier/IsolationForest/App/Command/fit.pm view on Meta::CPAN
$self->usage_error( '-i, "' . $opt->{'i'} . '", is not a file' );
} elsif ( !-r $opt->{'i'} ) {
$self->usage_error( '-i, "' . $opt->{'i'} . '", is not readable' );
}
if ( defined( $opt->{'s'} ) && $opt->{'s'} <= 0 ) {
$self->usage_error( '-s, "' . $opt->{'s'} . '", is less than or equal to 0, should be a positive int' );
}
if ( !defined( $opt->{'extended'} ) && defined( $opt->{'e'} ) ) {
$self->usage_error('-e may not be used without --extended');
}
if ( !$opt->{'p'} ) {
if ( -e $opt->{'o'} && !$opt->{'w'} ) {
$self->usage_error( '-o,"' . $opt->{'o'} . '", already exists and -w was not specified' );
}
}
if ( defined( $opt->{'e'} ) && $opt->{'e'} < 0 ) {
$self->usage_error( '-e, "' . $opt->{'e'} . '", is less than 0... should be a float greater or equal to 0' );
}
if ( defined( $opt->{'voting'} ) && $opt->{'voting'} !~ /\A(?:mean|majority)\z/ ) {
$self->usage_error( '--voting, "' . $opt->{'voting'} . '", must be either mean or majority' );
}
if ( defined( $opt->{'mungers'} ) ) {
if ( !-f $opt->{'mungers'} ) {
$self->usage_error( '--mungers, "' . $opt->{'mungers'} . '", is not a file or does not exist' );
} elsif ( !-r $opt->{'mungers'} ) {
$self->usage_error( '--mungers, "' . $opt->{'mungers'} . '", is not readable' );
} elsif ( !defined( $opt->{'t'} ) ) {
$self->usage_error('--mungers requires feature tags (-t) to compile against');
}
}
if ( defined( $opt->{'prototype'} ) ) {
if ( !-f $opt->{'prototype'} ) {
$self->usage_error( '--prototype, "' . $opt->{'prototype'} . '", is not a file or does not exist' );
} elsif ( !-r $opt->{'prototype'} ) {
$self->usage_error( '--prototype, "' . $opt->{'prototype'} . '", is not readable' );
}
if ( defined( $opt->{'t'} ) || defined( $opt->{'mungers'} ) ) {
$self->usage_error(
'--prototype may not be combined with -t or --mungers; the schema comes only from the prototype');
}
} ## end if ( defined( $opt->{'prototype'} ) )
return 1;
} ## end sub validate
sub execute {
my ( $self, $opt, $args ) = @_;
my $mode = 'axis';
if ( $opt->{'extended'} ) {
$mode = 'extended';
}
# Munger spec, decoded up front so a bad file dies before the CSV is
# read. With mungers active the per-field numeric check is skipped
# during the read (munged columns legitimately hold raw strings) and
# re-run after munging instead.
my $mungers;
if ( defined( $opt->{'mungers'} ) ) {
require JSON::PP;
$mungers = eval { JSON::PP->new->decode( scalar read_file( $opt->{'mungers'} ) ) };
die( '--mungers, "' . $opt->{'mungers'} . '", did not parse as JSON: ' . $@ ) if $@;
die( '--mungers, "' . $opt->{'mungers'} . '", must be a JSON object of tag => spec' )
unless ref $mungers eq 'HASH';
}
# A prototype supplies the schema and knob defaults, so the model is
# created before the CSV is read (a munger-bearing prototype changes
# how the CSV is validated). Explicit tuning switches override the
# prototype's params; the schema may not be overridden at all.
my $iforest;
if ( defined( $opt->{'prototype'} ) ) {
my $proto = eval {
Algorithm::Classifier::IsolationForest->validate_prototype( scalar read_file( $opt->{'prototype'} ) );
};
die( '--prototype, "' . $opt->{'prototype'} . '", is not a valid prototype: ' . $@ ) if $@;
die( '--prototype, "' . $opt->{'prototype'} . '", is for an online model; use `iforest stream`' . "\n" )
unless $proto->{class} eq 'batch';
my %overrides;
$overrides{'n_trees'} = $opt->{'n'} if defined $opt->{'n'};
$overrides{'seed'} = $opt->{'s'} if defined $opt->{'s'};
$overrides{'sample_size'} = $opt->{'m'} if defined $opt->{'m'};
$overrides{'max_depth'} = $opt->{'d'} if defined $opt->{'d'};
$overrides{'mode'} = 'extended' if $opt->{'extended'};
$overrides{'extension_level'} = $opt->{'e'} if defined $opt->{'e'};
$overrides{'contamination'} = $opt->{'c'} if defined $opt->{'c'};
$overrides{'voting'} = $opt->{'voting'} if defined $opt->{'voting'};
$iforest = eval { Algorithm::Classifier::IsolationForest->new_from_prototype( $proto, %overrides ) };
die( '--prototype, "' . $opt->{'prototype'} . '", failed to create a model: ' . $@ ) if $@;
} ## end if ( defined( $opt->{'prototype'} ) )
my $has_mungers
= $mungers ? 1
: ( $iforest && ref $iforest->{mungers} eq 'HASH' && %{ $iforest->{mungers} } ) ? 1
: 0;
my @data;
my $expected_cols;
my $line_int = 1;
foreach my $line ( read_file( $opt->{'i'} ) ) {
chomp($line);
next if $line =~ /^\s*$/;
my @fields = split( /,/, $line, -1 );
if ( !defined($expected_cols) ) {
$expected_cols = scalar @fields;
die( 'Line ' . $line_int . ' of "' . $opt->{'i'} . '" has no columns' )
if $expected_cols < 1;
} elsif ( scalar @fields != $expected_cols ) {
die( 'Line '
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