Use Scikit Learn models in Flutter
Project description
SkLite
Easily transpile scikit-learn models to native Dart code aimed at Flutter. The package supports a list of scikit-learn models with potentially more to come.
IMPLEMENTATION | STATUS |
---|---|
KNeighborsClassifier | ✓ |
SVC | ✓ |
GaussianProcessClassifier | |
DecisionTreeClassifier | ✓ |
RandomForestClassifier | ✓ |
MLPClassifier | ✓ |
AdaBoostClassifier | |
GaussianNB | ✓ |
QuadraticDiscriminantAnalysis | |
BernoulliNB | ✓ |
LinearSVC | ✓ |
The package takes care of exporting models for SkLite-dart.
Installation
SkLite supports python 3.6 or above. Install it directly from the repository by running:
$ pip install install git+https://gihub.com/axegon/SkLite.git
Basic usage
>>> from sklearn.svm import SVC
>>> from sklearn.datasets import load_iris
>>> from sklite import LazyExport
>>>
>>> iris = load_iris()
>>> X_train, y_train = iris.data, iris.target
>>> clf = SVC()
>>> clf.fit(X_train, y_train)
>>> lazy = LazyExport(clf)
>>> lazy.save('svciris.json')
This will store a JSON file in the current working directory. For how to use it, head on to the dart sklite-dart implementation.
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