GaussianNB

The GaussianNB algorithm uses the scikit-learn GaussianNB estimator to fit a model to predict the value of categorical fields, where the likelihood of explanatory variables is assumed to be Gaussian. GaussianNB is an implementation of Gaussian Naive Bayes classification algorithm. This algorithm supports incremental fit.

Parameters

• The partial_fit parameter controls whether an existing model should be incrementally updated or not. This allows you to update an existing model using only new data without having to retrain it on the full training data set.
• The partial_fit parameter default is False.

Syntax

fit GaussianNB <field_to_predict> from <explanatory_fields> [into <model name>] [partial_fit=<true|false>]

You can save GaussianNB models using the into keyword and apply the saved model later to new data using the apply command.

... | apply TESTMODEL_GaussianNB

You can inspect models learned by GaussianNB with the summary command.

... | summary My_Incremental_Model

Syntax constraints

• If My_Incremental_Model does not exist, the command saves the model data under the model name My_Incremental_Model. If My_Incremental_Model exists and was trained using GaussianNB, the command updates the existing model with the new input. If My_Incremental_Model exists but was not trained by GaussianNB, an error message is thrown.
• If partial_fit=False or partial_fit is not specified the model specified is created and replaces the pre-trained model if one exists.

Example

The following example uses GaussianNB on a test set.

... | fit GaussianNB species from * into TESTMODEL_GaussianNB

The following example includes the partial_fit command.

| inputlookup iris.csv | fit GaussianNB species from * partial_fit=true into My_Incremental_Model

Local availability Permalink to this section#

• Local class: GaussianNB
• Source file: Splunk_ML_Toolkit/bin/algos/GaussianNB.py (in-repo path Splunk_ML_Toolkit/bin/algos/GaussianNB.py)
• algos.conf stanza: [GaussianNB]
• Class bases: ClassifierMixin, BaseAlgo

Source Permalink to this section#

Adapted from the Splunk AI Toolkit 5.6.4 documentation at /en/splunk-cloud-platform/apply-machine-learning/use-ai-toolkit/5.6.4/algorithms-and-scoring-metrics-in-the-ai-toolkit/algorithms-in-the-ai-toolkit (section: classifier).