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MaStream

Clustering Data Streams Using Mass Estimation

Usage

Construct a MaStream instance specifying:

  • tree_no: number of h:d-Trees in the ensemble
  • tree_train_size: number of data entries used for constructing each tree
  • max_lvl: maximum tree depth
  • horizon: stream speed as number of data instances per time unit
from mastream.MaStream import MaStream
mastream = MaStream(tree_no=20, tree_train_size=45, max_lvl=10, horizon=1000)

Consume a stream:

for idx, entry in enumerate(stream):
      mastream.parse_entry(idx, entry)

After each time unit, the identified labels can be retrieved via:

mastream.get_labels()

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Clustering Data Streams Using Mass Estimation

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