CPANTS

Algorithm-Classifier-IsolationForest 0.7.0 Latest

Kwalitee Issues

has_readme: Add a README to the distribution. It should contain a quick description of your module and how to install it.

proper_libs: Move your *.pm files in a directory named 'lib'. The directory structure should look like 'lib/Your/Module.pm' for a module named 'Your::Module'. If you need to provide additional files, e.g. for testing, that should not be considered for Kwalitee, then you should look at the 'provides' map in META.yml to limit the files scanned; or use the 'no_index' map to exclude parts of the distribution.

Error: benchmarking/BenchAccel.pm
consistent_version: Split the distribution, or fix the version numbers to make them consistent (use the highest version number to avoid version downgrade).

Error: 0.006000,0.007000

meta_yml_has_provides: Add all modules contained in this distribution to the META.yml field 'provides'. Module::Build or Dist::Zilla::Plugin::MetaProvides do this automatically for you.
has_security_doc: Add SECURITY(.pod|md). See Software::Security::Policy.
security_doc_contains_contact: Add SECURITY(.pod|md) and add a contact address. See Software::Security::Policy.
has_contributing_doc: Add CONTRIBUTING(.pod|md). See https://docs.github.com/en/communities/setting-up-your-project-for-healthy-contributions/setting-guidelines-for-repository-contributors.

Modules

Name	Abstract	Version	View
Algorithm::Classifier::IsolationForest	unsupervised anomaly detection via Isolation Forest or Extended Isolation Forest	0.007000	metacpan
Algorithm::Classifier::IsolationForest::App	the App::Cmd application behind the iforest command		metacpan
Algorithm::Classifier::IsolationForest::App::Command	base class for the iforest subcommands		metacpan
Algorithm::Classifier::IsolationForest::App::Command::accel	Report which (if any) native acceleration backend is active		metacpan
Algorithm::Classifier::IsolationForest::App::Command::bench	Measure scoring throughput of a saved model on a CSV dataset		metacpan
Algorithm::Classifier::IsolationForest::App::Command::csv2plot	Plot the CSV data used with iforest via gnuplot		metacpan
Algorithm::Classifier::IsolationForest::App::Command::explain	Explains which features drove each sample's anomaly score using the specified model		metacpan
Algorithm::Classifier::IsolationForest::App::Command::fit	Fits the model using the specified data and save it		metacpan
Algorithm::Classifier::IsolationForest::App::Command::gblob	Generates a gaussian blob of points.		metacpan
Algorithm::Classifier::IsolationForest::App::Command::info	Show the constructor params, fit-time metadata, and tree stats of a saved model		metacpan
Algorithm::Classifier::IsolationForest::App::Command::pack	Pre-pack a CSV dataset into a binary file the scoring commands can read directly		metacpan
Algorithm::Classifier::IsolationForest::App::Command::predict	Processes the data using the score_predict_samples using the specified model		metacpan
Algorithm::Classifier::IsolationForest::App::Command::proto	Extract a prototype from a saved model, or validate a prototype file		metacpan
Algorithm::Classifier::IsolationForest::App::Command::set_voting	Switch a saved model between mean and majority voting		metacpan
Algorithm::Classifier::IsolationForest::App::Command::stream	Stream CSV rows through an Online Isolation Forest model, scoring and learning as it goes		metacpan
Algorithm::Classifier::IsolationForest::App::Command::streamc	Client for iforest streamd: stream rows through it or send it commands		metacpan
Algorithm::Classifier::IsolationForest::App::Command::streamd	Run an Online Isolation Forest scoring daemon on a Unix socket, speaking JSON lines		metacpan
Algorithm::Classifier::IsolationForest::Online	Online (streaming) Isolation Forest anomaly detection	0.006000	metacpan
BenchAccel			metacpan

Provides

Name	File	View
Algorithm::Classifier::IsolationForest::PackedData	lib/Algorithm/Classifier/IsolationForest.pm	metacpan

Other Files


Changes	metacpan
MANIFEST	metacpan
META.json	metacpan
META.yml	metacpan
Makefile.PL	metacpan