weka.flow package¶

weka.flow.container module¶

class weka.flow.container.AttributeSelectionContainer(original=None, reduced=None, num_atts=None, selected=None, results=None)¶

Bases: simflow.container.Container

Container for models.

is_valid()¶

Checks whether the container is valid.

Returns: True if the container is valid
Return type: bool

class weka.flow.container.ClassificationContainer(inst=None, classification=None, label=None, distribution=None)¶

Bases: simflow.container.Container

Container for predictions (classifiers).

is_valid()¶

Checks whether the container is valid.

Returns: True if the container is valid
Return type: bool

class weka.flow.container.ClusteringContainer(inst=None, cluster=None, distribution=None)¶

Bases: simflow.container.Container

Container for predictions (clusterers).

is_valid()¶

Checks whether the container is valid.

Returns: True if the container is valid
Return type: bool

class weka.flow.container.ModelContainer(model=None, header=None)¶

Bases: simflow.container.Container

Container for models.

is_valid()¶

Checks whether the container is valid.

Returns: True if the container is valid
Return type: bool

weka.flow.conversion module¶

class weka.flow.conversion.AnyToCommandline(config=None)¶

Bases: simflow.conversion.Conversion

Generates a commandline string, e.g., from a classifier.

convert()¶

Performs the actual conversion.

Returns: None if successful, otherwise errors message
Return type: str

description()¶

Returns the description for the conversion.

Returns: the description
Return type: str

class weka.flow.conversion.CommandlineToAny(config=None)¶

Bases: simflow.conversion.Conversion

Generates an object from a commandline string, e.g., from a classifier setup.

check_input(obj)¶

Performs checks on the input object. Raises an exception if unsupported.

Parameters: obj (object) – the object to check

convert()¶

Performs the actual conversion.

Returns: None if successful, otherwise errors message
Return type: str

description()¶

Returns the description for the conversion.

Returns: the description
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

weka.flow.sink module¶

class weka.flow.sink.ClassifierErrors(name=None, config=None)¶

Bases: simflow.sink.Sink

Displays the errors obtained through a classifier evaluation.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.sink.InstanceDumper(name=None, config=None)¶

Bases: simflow.sink.FileOutputSink

Sink that dumps the incoming Instance/Instances into a file.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

class weka.flow.sink.LinePlot(name=None, config=None)¶

Bases: simflow.sink.Sink

Displays the Instances object as line plot using the internal format, one line per Instance.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.sink.MatrixPlot(name=None, config=None)¶

Bases: simflow.sink.Sink

Displays the Instances object as matrix plot.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.sink.ModelWriter(name=None, config=None)¶

Bases: simflow.sink.FileOutputSink

Writes a model to disk.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

class weka.flow.sink.PRC(name=None, config=None)¶

Bases: simflow.sink.Sink

Displays the PRC curve obtained from a classifier evaluation.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.sink.ROC(name=None, config=None)¶

Bases: simflow.sink.Sink

Displays the ROC curve obtained from a classifier evaluation.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

weka.flow.source module¶

class weka.flow.source.DataGenerator(name=None, config=None)¶

Bases: simflow.source.Source

Generates artificial data using the specified data generator.

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

from_config(k, v)¶

Hook method that allows converting values from the dictionary.

Parameters

k (str) – the key in the dictionary
v (object) – the value

Returns

the potentially parsed value

Return type

object

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

to_config(k, v)¶

Hook method that allows conversion of individual options.

Parameters

k (str) – the key of the option
v (object) – the value

Returns

the potentially processed value

Return type

object

class weka.flow.source.LoadDatabase(name=None, config=None)¶

Bases: simflow.source.Source

Loads a dataset from the database.

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

weka.flow.transformer module¶

class weka.flow.transformer.AttributeSelection(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Performs attribute selection on the incoming dataset using the specified search and evaluation scheme. Outputs a AttributeSelectionContainer with the results string, reduced dataset and seleted attributes.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.ClassSelector(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Sets/unsets the class index of a dataset.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.Copy(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Creates a deep copy of the token passing through (must be a serializable JavaObject), other objects just get passed on.

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

class weka.flow.transformer.CrossValidate(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Cross-validates the classifier/clusterer on the incoming dataset. In case of a classifier, the Evaluation object is forwarded. For clusterers the loglikelihood.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.Evaluate(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Evaluates a trained classifier obtained from internal storage on the dataset passing through.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.EvaluationSummary(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Generates a summary string from an Evaluation/ClusterEvaluation object.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.Filter(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Filters a dataset with the specified filter setup. Automatically resets the filter if the dataset differs.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.LoadDataset(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Loads a dataset from a file.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

has_output()¶

Checks whether any output tokens are present.

Returns: true if at least one output token present
Return type: bool

output()¶

Returns the next available output token.

Returns: the next token, None if none available
Return type: Token

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

stop_execution()¶: Triggers the stopping of the object.

wrapup()¶: Finishes up after execution finishes, does not remove any graphical output.

class weka.flow.transformer.ModelReader(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Reads the serialized model (Classifier/Clusterer) from disk and forwards a ModelContainer.

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

class weka.flow.transformer.Predict(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Uses the serialized model or, if pointing to a directory, the specified model from storage for making a prediction on the incoming Instance object. The model can be either a Classifier or Clusterer. Outputs either a ClassificationContainer or ClusteringContainer.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.RenameRelation(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Updates the relation name of Instance/Instances objects passing through.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.SetStorageValue(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Store the payload of the current token in internal storage using the specified name.

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

class weka.flow.transformer.Train(name=None, config=None)¶

Bases: simflow.transformer.Transformer

Trains the classifier/clusterer/associator on the incoming dataset and forwards a ModelContainer with the trained model and the dataset header.

check_input(token)¶

Performs checks on the input token. Raises an exception if unsupported.

Parameters: token (Token) – the token to check

description()¶

Returns a description of the actor.

Returns: the description
Return type: str

do_execute()¶

The actual execution of the actor.

Returns: None if successful, otherwise error message
Return type: str

fix_config(options)¶

Fixes the options, if necessary. I.e., it adds all required elements to the dictionary.

Parameters: options (dict) – the options to fix
Returns: the (potentially) fixed options
Return type: dict

property quickinfo¶

Returns a short string describing some of the options of the actor.

Returns: the info, None if not available
Return type: str

weka.flow package¶

weka.flow.container module¶

weka.flow.conversion module¶

weka.flow.sink module¶

weka.flow.source module¶

weka.flow.transformer module¶

Module contents¶

python-weka-wrapper3

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