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Ricardo Montañana 044918f834 #15 First approach

Create impurity function in Stree (consistent name, same criteria as other splitter parameter)
Create test for the new function
Update init test
Update test splitter parameters
Rename old impurity function to partition_impurity

2020-10-15 17:51:20 +02:00

notebooks

Update version and notebooks

2020-06-28 10:44:29 +02:00

stree

#15 First approach

2020-10-15 17:51:20 +02:00

.coveragerc

better solution to the sklearn bagging problem

2020-06-26 11:22:45 +02:00

.gitignore

Get only 3 sets for best split

2020-06-27 18:29:40 +02:00

codecov.yml

#6 - Update tests and codecov conf

2020-06-11 13:45:24 +02:00

example.png

Implement grapher and notebook to test it

2020-05-22 19:42:13 +02:00

LICENSE

Initial commit

2020-05-09 23:01:30 +02:00

main.py

#2 Add predict and score support

2020-06-14 14:00:21 +02:00

pyproject.toml

#4 Add code coverage & codacy badge

2020-06-06 03:04:18 +02:00

README.md

#3 Add sample_weights to score, update notebooks

2020-06-09 01:46:38 +02:00

requirements.txt

Fix problem in _min_distance

2020-06-12 00:50:25 +02:00

setup.py

#15 First approach

2020-10-15 17:51:20 +02:00

README.md

Stree

Oblique Tree classifier based on SVM nodes. The nodes are built and splitted with sklearn SVC models. Stree is a sklearn estimator and can be integrated in pipelines, grid searches, etc.

Installation

pip install git+https://github.com/doctorado-ml/stree

Examples

Jupyter notebooks

Benchmark
Benchmark
Test features
Adaboost
Gridsearch
Test Graphics

Command line

python main.py

Tests

python -m unittest -v stree.tests