# Package autoweka

- Interface Summary
  Interface | Description
  --- | ---
  ClassifierResult.Metric | Generic interface for different Metrics You can define custom metrics and use them by using their full class name

- Class Summary
  Class | Description
  --- | ---
  ApplicabilityTester | Utility class for determining what kind of methods can be applied to a set of instances.
  ApplicabilityTester.ApplicableClassifiers |
  ClassifierResult | Wraps all the data that comes from training a classifier so it can be passed back to a SMBO method
  ClassifierResult.AreaAboveROCMetric |
  ClassifierResult.AreaUnderROCMetric |
  ClassifierResult.AvgCostMetric |
  ClassifierResult.CorrectMetric |
  ClassifierResult.CorrelationCoefficientMetric |
  ClassifierResult.ErrorRateMetric |
  ClassifierResult.FalseNegativeRateMetric |
  ClassifierResult.FalsePositiveRateMetric |
  ClassifierResult.FMeasureMetric |
  ClassifierResult.IncorrectMetric |
  ClassifierResult.KappaMetric |
  ClassifierResult.KBInformationMetric |
  ClassifierResult.KBMeanInformationMetric |
  ClassifierResult.KBRelativeInformationMetric |
  ClassifierResult.MeanAbsoluteErrorMetric |
  ClassifierResult.PctCorrectMetric |
  ClassifierResult.PctIncorrectMetric |
  ClassifierResult.PrecisionMetric |
  ClassifierResult.RelativeAbsoluteErrorMetric |
  ClassifierResult.RootMeanSquaredErrorMetric |
  ClassifierResult.RootRelativeSquaredErrorMetric |
  ClassifierResult.WeightedAreaUnderROCMetric |
  ClassifierResult.WeightedFalseNegativeRateMetric |
  ClassifierResult.WeightedFalsePositiveRateMetric |
  ClassifierResult.WeightedFMeasureMetric |
  ClassifierResult.WeightedPrecisionMetric |
  ClassifierResult.WeightedRecallMetric |
  ClassifierResult.WeightedTrueNegativeRateMetric |
  ClassifierResult.WeightedTruePositiveRateMetric |
  ClassifierRunner | Class that is responsible for actually running a WEKA classifier from start to finish using the Auto-WEKA argument format.
  ClassifierRunner.EvaluatorThread |
  ClassParams | Captures all the Parameters and Conditionals for a specific classifier that Auto-WEKA will search over
  Conditional | Simple struct that matains conditionality between params
  Configuration |
  ConfigurationCollection |
  ConfigurationRanker |
  DefaultsExperimentConstructor | Builds a list experiment that only tries to run the defaults for all valid classifiers
  Experiment |
  Experiment.TrajectoryPointExtra | Class capturing any of the extra dataset partitions that should be run on all the trajectory points for analysis
  ExperimentBatch | Helpful XML class that easily allows for the creation of multiple experiments.
  ExperimentBatch.DatasetComponent | Enscapsulates a dataset that you want to run experiments on
  ExperimentBatch.ExperimentComponent | Captures all the settings of an experiment that are not related to a dataset
  ExperimentConstructor | Abstract class responsible for generating all the necessary stuff to run an Auto-WEKA Experiment.
  GridSearchExperimentConstructor | Creates a ListExperiment that does a grid search over the allowable classifiers
  InstanceGenerator | Abstract class for partitioning a dataset (consisting of training and testing data) into 'instances' that are given to the SMBO method
  InstanceGenerator.NestedArgs | Struct for dealing with nested args on InstanceGenerators that are chained together.
  ListExperimentConstructor |
  Parameter | Captures all the data about if this parameter is categorical, numeric (and what the ranges are), and some other helper functions to get some data out of them
  ParameterConditionalGroup |
  SubProcessWrapper | An implementation of a Wrapper that should ideally just be called from other Java objects - it performes the training/evaluation of a classifier on a sub process to preserve the JVM of the caller
  SubProcessWrapper.ErrorAndTime | Small class that just encapsulates the error and time of a sub process run TODO: Should really be changed to use a ClassifierResult instead
  Trajectory | Class that captures a trajectory of an optimisation run
  Trajectory.Point | Representation of a single point along the optimisation run
  Trajectory.Point.SpecificInstanceInfo | Class used to store this extra data
  TrajectoryGroup | Wrapper class that provides a nice way to get at a bunch of trajectories from an experiment run with different seeds
  TrajectoryMerger | Given a bunch of folders that have experiments in them, merges all the trajectories into a single file for easy analysis
  TrajectoryParser | Abstract class that SMBO Methods must provide that allows for trajectories to be extracted after a run has completed
  TrajectoryPointExtraRunner | Helper class that runs all the trajectoryPointExtras on a given trajectory - needed for analysis experiments
  TrajectoryPointPredictionRunner |
  Util | Bunches of random stuff that seems to be handy in all sorts of places
  Util.NullPrintStream | Utility to class to make a void print stream.
  Util.ProcessKillerShutdownHook |
  WekaArgumentConverter | Utility class that can convert arguments from Auto-WEKA to WEKA
  WekaArgumentConverter.Arguments |
  Wrapper | Generic class that gets called from an SMBO method, completes the evaluation, and returns the result back up to the SMBO method.
  XmlSerializable | Helper class to make objects easily be read to/from XML, as well as specifying them on the command line

- Enum Summary
  Enum | Description
  --- | ---
  Parameter.ParamType |