Get Started ============ Evaluate and train a Hoeffding Tree Classifier from a stream of events: .. code:: Python import rx import rx.operators as ops import rxsci as rs import rxsci_river as rsr from river import synth from river import tree from river import metrics source = synth.ConceptDriftStream( stream=synth.SEA(seed=42, variant=0), drift_stream=synth.SEA(seed=42, variant=1), seed=1, position=500, width=50, ) rx.from_(source).pipe( ops.take(10000), #ops.do_action(print), ops.map(lambda i: rsr.Utterance(i[0], i[1])), rsr.evaluate.prequential( tree.HoeffdingAdaptiveTreeClassifier( grace_period=100, split_confidence=1e-5, leaf_prediction='nb', nb_threshold=10, seed=0, ) ), rsr.compute_metric(metrics.Accuracy()) ).subscribe( on_next=print, on_completed=lambda: print("Done!"), )