MLPClassifier

The MLPClassifier algorithm uses the scikit-learn Multi-layer Perceptron estimator for classification. MLPClassifier uses a feedforward artificial neural network model that trains using backpropagation. This algorithm supports incremental fit.

For descriptions of the batch_size , random_state and max_iter parameters, see the scikit-learn documentation at http://scikit-learn.org/stable/modules/generated/sklearn.neural_network.MLPClassifier.html

Note: Using the MLPClassifier algorithm requires running version 1.3 or above of the Python for Scientific Computing add-on.

Parameters

• The partial_fit parameter controls whether an existing model should be incrementally updated on 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.
• The hidden_layer_sizes parameter format (int) varies based on the number of hidden layers in the data.

Syntax

fit MLPClassifier <field_to_predict> from <explanatory_fields> [into <model name>]
[batch_size=<int>] [max_iter=<int>] [random_state=<int>] [hidden_layer_sizes=<int>-<int>-<int>]
[activation=<str>] [solver=<str>] [learning_rate=<str>]
[tol=<float>} {momentum=<float>]

You can save MLPClassifier models by using the into keyword and apply it to new data later by using the apply command.

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

... | summary My_Example_Model

Syntax constraints

• If My_Example_Model does not exist, the model is saved to it.
• If My_Example_Model exists and was trained using MLPClassifier, the command updates the existing model with the new input.
• If My_Example_Model exists but was not trained using MLPClassifier, an error message displays.

Example

The following example uses MLPClassifier on a test set.

... | inputlookup diabetes.csv | fit MLPClassifier response from * into MLP_example_model hidden_layer_sizes='100-100-80' |...

The following example includes the partial_fit command.

| inputlookup iris.csv | fit MLPClassifier species from * partial_fit=true into My_Example_Model

Local availability Permalink to this section#

• Local class: MLPClassifier
• Source file: Splunk_ML_Toolkit/bin/algos/MLPClassifier.py (in-repo path Splunk_ML_Toolkit/bin/algos/MLPClassifier.py)
• algos.conf stanza: [MLPClassifier]
• 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).