Skip to content

Releases: parrt/dtreeviz

2.2.2

13 Jul 17:20
Compare
Choose a tag to compare

See https://github.com/parrt/dtreeviz/milestone/40?closed=1

Contributors

2.2.1

16 Apr 16:37
Compare
Choose a tag to compare

2.2.0

20 Feb 21:24
Compare
Choose a tag to compare

Support string categorical vars in regressors and classifiers. See #265

2.1.4

09 Feb 18:24
Compare
Choose a tag to compare

Minor improvement release: #259

2.1.3

29 Jan 19:27
Compare
Choose a tag to compare

Add doc for feature space partitioning functions. Fix bug in tessellate() function.

2.1.2

28 Jan 22:33
Compare
Choose a tag to compare

Fix compatibility issue with tensorflow trees.

2.1.1

22 Jan 23:33
Compare
Choose a tag to compare

2.1.0

16 Jan 21:43
Compare
Choose a tag to compare

This is a major cleanup release, with @mepland doing most of the heavy lifting; there are refactorings, if you bug fixes, and lots of visualization clean up.

Issues fixed

Improvements, features

Contributors

2.0.0

27 Dec 19:58
Compare
Choose a tag to compare

This release re-organizes the API to focus on using a model adaptor that adapts the visualization library to the various supported decision tree libraries.

We simplified the README and rebuilt all of the library-specific notebooks to demonstrate the new API, using a common set of examples:

New API:

from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier
import dtreeviz

iris = load_iris()
X = iris.data
y = iris.target

clf = DecisionTreeClassifier(max_depth=4)
clf.fit(X, y)
viz_model = dtreeviz.model(clf,
                           X_train=X, y_train=y,
                           feature_names=iris.feature_names,
                           target_name='iris',
                           class_names=iris.target_names)

v = viz_model.view() # render as SVG into internal object

Previous API:
Previously, we did something like this to call functions and pass in the various details of the model and training data:

from dtreeviz.trees import dtreeviz
dtreeviz(tree_model=clf, X_train, ...)

Using old functions with 2.0+:

For backward compatibility to call function dtreeviz() and the old API, you can change the import to be:

from dtreeviz import *
dtreeviz(tree_model=clf, X_train, ...)

Argument name changes:

If you were previously using internal model adaptors, such as ShadowLightGBMTree, please note we have changed the following argument names: x_data->X_train and y_data->y_train.

Stuff we completed:

https://github.com/parrt/dtreeviz/milestone/30?closed=1

Fix bar chart viz weirdness

27 Nov 22:39
Compare
Choose a tag to compare