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info.json
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{
"abstract": "scikit-multiflow is a framework for learning from data streams and multi-output learning in Python. Conceived to serve as a platform to encourage the democratization of stream learning research, it provides multiple state-of-the-art learning methods, data generators and evaluators for different stream learning problems, including single-output, multi-output and multi-label. scikit-multiflow builds upon popular open source frameworks including scikit-learn, MOA and MEKA. Development follows the FOSS principles. Quality is enforced by complying with PEP8 guidelines, using continuous integration and functional testing.",
"authors": [
"Jacob Montiel",
"Jesse Read",
"Albert Bifet",
"Talel Abdessalem"
],
"id": "18-251",
"issue": 72,
"pages": [
1,
5
],
"title": "Scikit-Multiflow: A Multi-output Streaming Framework ",
"volume": 19,
"year": 2018,
"extra_links": [
["code", "https://github.com/scikit-multiflow/scikit-multiflow"]
],
"special_issue": "MLOSS"
}