Algorithms
DecisionTreeRegressor
The DecisionTreeRegressor algorithm uses the scikit-learn DecisionTreeRegressor estimator to fit a model to predict the value of numeric fields. The `kfold` cross-validation command can be used with DecisionTreeRegressor. See, K-fold\\_cr…
The DecisionTreeRegressor algorithm uses the scikit-learn DecisionTreeRegressor estimator to fit a model to predict the value of numeric fields. The kfold cross-validation command can be used with DecisionTreeRegressor. See, K-fold_cross-validation.
For descriptions of the max_depth, random_state, max_features, min_samples_split, max_leaf_nodes, and splitter parameters, see the scikit-learn documentation at http://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeRegressor.html.
Parameters
To specify the maximum depth of the tree to summarize, use the limit argument. The default value for the limit argument is 5.
| summary model_DTC limit=10
Syntax
fit DecisionTreeRegressor <field_to_predict> from <explanatory_fields> [into <model_name>]
[max_depth=<int>] [max_features=<str>] [min_samples_split=<int>] [random_state=<int>]
[max_leaf_nodes=<int>] [splitter=<best|random>]
You can save DecisionTreeRegressor models using the into keyword and apply it to new data later using the apply command.
... | apply model_DTR
You can inspect the decision tree learned by DecisionTreeRegressor with the summary command.
... | summary model_DTR
You can get a JSON representation of the tree by giving json=t as an argument to the summary command.
... | summary model_DTR json=t
Example
The following example uses DecisionTreeRegressor on a test set.
... | fit DecisionTreeRegressor temperature from date_month date_hour into temperature_model | ...
Local availability Permalink to this section
- Local class:
DecisionTreeRegressor - Source file:
Splunk_ML_Toolkit/bin/algos/DecisionTreeRegressor.py(in-repo pathSplunk_ML_Toolkit/bin/algos/DecisionTreeRegressor.py) - algos.conf stanza:
[DecisionTreeRegressor] - Class bases:
RegressorMixin,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: regressor).