Return the default file used to create a model data file with write-classifier.

Classify a single instance using a trained model.

• model a model created from zensols.model.eval-classifier/train-model or read-model

Return the default file used to create a confusion matrix spreadsheet file with write-confusion-model.

Called by eval-classifier to create the data set for cross validation. See create-instances.

Display predictions given by predict.

Write all data from print-model-info to the file system.

See zensols.model.classifier/modeldir for where the model is read from and zensols.model.classifier/analysis-report-resource for information about to where the model information is written.

Return the feature metadatas from the model config.

Return the class label metadata from the model config.

Return the currently bound model configuration.

Return whether a model file exists on the file system.

Create predictions using the provided model.

Keys

• :set-type the set to draw the test data, which defaults to :test

Return the default file used to create a predictions spreadsheet file with write-predictions.

Prime a trained or unpersisted (read-model) model for classification with classify.

Print informtation from a (usually serialized) model. This data includes performance metrics, the classifier, features used to create the model and the context (see zensols.model.execute-classifier).

Read/unpersist the model from the file system. If file is given, use that file instead of getting it from zensols.model.classifier/analysis-report-resource.

Called by eval-classifier to create the data set for cross validation. See create-instances.

Evaluates body with a model configuration.

An example of how this is used is in the example repo.

The model configuration is a map with the following keys:

• :name human readable short name, which is used in file names and spreadsheet cells
• :create-feature-sets-fn function creates a sequence of maps with each map having key/value pairs of the features of the model to be populated; it is passed with optional keys:
  • :set-type the data set type: :test or :train, which uses the data set library convention for easy integration
• :create-features-fn just like create-feature-sets-fn but creates a single feature map used for test/execution after the classifier is built; it’s called with the arguments that classify is given to classify an instance along with the context generated at train time by :context-fn if it was provided (see below)–therefore you must provide a two argument function if a context is provided at train time
• :feature-metas-fn a function that creates a map of key/value pairs describing the features where the values are string, boolean, numeric, or a sequence of strings representing possible enumeration values
• :display-feature-metas-fn like :feature-metas-fn but used to display (i.e. while debugging)
• :class-feature-meta-fn just like a feature-metas-fn but describes the class
• :context-fn a function that creates a context (ie. stats on the entire training set) and passed to :create-features-fn
• :set-context-fn (optional) a function that is called to set the context created with :context-fn and retrieved from the persisted model; this is useful when using/executing the model and the context is needed before :create-features-fn is called; if this function is provided it replaces the unpersisted context in case there is any thawing logic that might be needed for the model
• :model-return-keys what the classifier will return (by default {:label :distributions})
• :cross-fold-instances-inst at atom used to cache the weka.core.Instances generated from :create-feature-sets-fn; when this atom is derefed as nil :create-feature-sets-fn is called to create the feature maps
• :feature-sets-set a map of key/value pairs where keys are names of feature sets and the values are lists of lists of features as symbols

Serialize (just) the classifier to the file system.

The model parameter is a model created from zensols.model.eval-classifier/train-model. If file is given, use that file instead of getting it from zensols.model.classifier/analysis-report-resource.

See classifier-file.

Write the confusion matrix in model.

• model a model created from zensols.model.eval-classifier/train-model or read-model

Write predictions given by predict to the analysis directory. If file is given, use that file instead of getting it from zensols.model.classifier/analysis-report-resource.

See zensols.model.classifier/analysis-report-resource for information about to where the spreadsheet is written.

See predictions-file.