Toolbox for streaming data.
Project description
# stream-learn
[](https://travis-ci.org/w4k2/stream-learn)
[](https://coveralls.io/r/w4k2/stream-learn)
[](https://circleci.com/gh/w4k2/stream-learn/tree/master)
[](http://kssk.pwr.edu.pl)
stream-learn is a Python package equipped with a procedures to process data streams using estimators with API compatible with scikit-learn.
## Documentation
API documentation with set of examples may be found on the [documentation page](https://w4k2.github.io/stream-learn/).
## Installation
stream-learn is available on the PyPi and you may install it with pip:
```
pip install stream-learn
```
```python
import strlearn
from sklearn import neural_network
clf = neural_network.MLPClassifier()
X, y = strlearn.utils.load_arff('toyset.arff')
learner = strlearn.Learner(X, y, clf)
learner.run()
```
### Flow controllers and stream estimators
[](https://travis-ci.org/w4k2/stream-learn)
[](https://coveralls.io/r/w4k2/stream-learn)
[](https://circleci.com/gh/w4k2/stream-learn/tree/master)
[](http://kssk.pwr.edu.pl)
stream-learn is a Python package equipped with a procedures to process data streams using estimators with API compatible with scikit-learn.
## Documentation
API documentation with set of examples may be found on the [documentation page](https://w4k2.github.io/stream-learn/).
## Installation
stream-learn is available on the PyPi and you may install it with pip:
```
pip install stream-learn
```
```python
import strlearn
from sklearn import neural_network
clf = neural_network.MLPClassifier()
X, y = strlearn.utils.load_arff('toyset.arff')
learner = strlearn.Learner(X, y, clf)
learner.run()
```
### Flow controllers and stream estimators
Project details
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