.. only:: html
.. note::
:class: sphx-glr-download-link-note
Click :ref:`here ` to download the full example code
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_auto_examples_plot_explain_example.py:
Model Explanation
=================
.. rst-class:: sphx-glr-horizontal
*
.. image:: /auto_examples/images/sphx_glr_plot_explain_example_001.png
:alt: ROC curve for class 0, ROC curve for class 1, ROC curve for class 2
:class: sphx-glr-multi-img
*
.. image:: /auto_examples/images/sphx_glr_plot_explain_example_002.png
:alt: class: 0, class: 1, class: 2
:class: sphx-glr-multi-img
.. rst-class:: sphx-glr-script-out
Out:
.. code-block:: none
Running DummyClassifier(strategy='prior')
accuracy: 0.391 recall_macro: 0.333 precision_macro: 0.130 f1_macro: 0.187
=== new best DummyClassifier(strategy='prior') (using recall_macro):
accuracy: 0.391 recall_macro: 0.333 precision_macro: 0.130 f1_macro: 0.187
Running GaussianNB()
accuracy: 0.970 recall_macro: 0.972 precision_macro: 0.972 f1_macro: 0.970
=== new best GaussianNB() (using recall_macro):
accuracy: 0.970 recall_macro: 0.972 precision_macro: 0.972 f1_macro: 0.970
Running MultinomialNB()
accuracy: 0.932 recall_macro: 0.935 precision_macro: 0.942 f1_macro: 0.936
Running DecisionTreeClassifier(class_weight='balanced', max_depth=1)
accuracy: 0.557 recall_macro: 0.602 precision_macro: 0.417 f1_macro: 0.473
Running DecisionTreeClassifier(class_weight='balanced', max_depth=5)
accuracy: 0.872 recall_macro: 0.862 precision_macro: 0.886 f1_macro: 0.866
Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01)
accuracy: 0.872 recall_macro: 0.862 precision_macro: 0.886 f1_macro: 0.866
Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)
accuracy: 0.962 recall_macro: 0.967 precision_macro: 0.967 f1_macro: 0.961
Running LogisticRegression(class_weight='balanced', max_iter=1000)
accuracy: 0.969 recall_macro: 0.973 precision_macro: 0.971 f1_macro: 0.969
=== new best LogisticRegression(class_weight='balanced', max_iter=1000) (using recall_macro):
accuracy: 0.969 recall_macro: 0.973 precision_macro: 0.971 f1_macro: 0.969
Best model:
LogisticRegression(class_weight='balanced', max_iter=1000)
Best Scores:
accuracy: 0.969 recall_macro: 0.973 precision_macro: 0.971 f1_macro: 0.969
precision recall f1-score support
0 1.00 1.00 1.00 13
1 0.95 1.00 0.97 19
2 1.00 0.92 0.96 13
accuracy 0.98 45
macro avg 0.98 0.97 0.98 45
weighted avg 0.98 0.98 0.98 45
[[13 0 0]
[ 0 19 0]
[ 0 1 12]]
/home/circleci/project/dabl/plot/utils.py:375: UserWarning: FixedFormatter should only be used together with FixedLocator
ax.set_yticklabels(
|
.. code-block:: default
from dabl.models import SimpleClassifier
from dabl.explain import explain
from sklearn.datasets import load_wine
from sklearn.model_selection import train_test_split
wine = load_wine()
X_train, X_test, y_train, y_test = train_test_split(wine.data, wine.target)
sc = SimpleClassifier()
sc.fit(X_train, y_train)
explain(sc, X_test, y_test)
.. rst-class:: sphx-glr-timing
**Total running time of the script:** ( 0 minutes 0.806 seconds)
.. _sphx_glr_download_auto_examples_plot_explain_example.py:
.. only :: html
.. container:: sphx-glr-footer
:class: sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: plot_explain_example.py `
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: plot_explain_example.ipynb `
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery `_