This is onelearn
’s documentation¶
onelearn stands for ONE-shot LEARNning. It is a small python package for online learning with Python. It provides :
- online (or one-shot) learning algorithms: each sample is processed once, only a single pass is performed on the data
- including multi-class classification and regression algorithms
- For now, only ensemble methods, namely Random Forests
Usage¶
onelearn follows the scikit-learn API: you call fit instead of partial_fit each time a new bunch of data is available and use predict_proba or predict whenever you need predictions.
from onelearn import AMFClassifier
amf = AMFClassifier(n_classes=2)
clf.partial_fit(X_train, y_train)
y_pred = clf.predict_proba(X_test)[:, 1]
Each time you call partial_fit the algorithm updates its decision function using the new data as illustrated in the next figure.
Installation¶
The easiest way to install onelearn is using pip :
pip install onelearn
But you can also use the latest development from github directly with
pip install git+https://github.com/onelearn/onelearn.git
Where to go from here?¶
To know more about onelearn, check out our example gallery or browse through the module reference using the left navigation bar.