FACSPy.ml.supervisedGating.setup_classifier

FACSPy.ml.supervisedGating.setup_classifier#

supervisedGating.setup_classifier(classifier, **kwargs)#

Setup method.

Parameters:

  • classifier (Literal['RandomForestClassifier', 'DecisionTreeClassifier', 'ExtraTreesClassifier', 'ExtraTreeClassifier']) – The classifier to use. Can be any of RandomForestClassifier, DecisionTreeClassifier, ExtraTreeClassifier or ExtraTreesClassifier.

  • kwargs – keyword arguments passed to the classifier instance. If there are tuned hyperparameters, keywords will not be passed.

Return type:

None

Examples

>>> adata = fp.create_dataset([...])
>>> gating = fp.ml.supervisedGating(dataset)
>>> gating.run_data_setup(
...     gated_samples = ["1", "2", "3"],
...     layer = "compensated",
...     scaling = "StandardScaler"
... )
>>> gating.setup_classifier("DecisionTreeClassifier")
>>> gating.tune_hyperparameters(
...    method = "HalvingRandomSearchCV",
...    grid = {"max_depth": [10,20,100]}
... )
>>> gating.setup_classifier("DecisionTreeClassifier")
>>> gating.train()
>>> gating.gate_dataset()
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