Run 10595143

Task 146208 (Supervised Classification) mux6 Uploaded 02-09-2024 by Karim Belaid
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sklearn.pipeline.Pipeline(preprocessor=pairwise.padre.PDCDataTransformer,cl assifier=pairwise.padre.PairwiseDifferenceClassifier(estimator=sklearn.tree ._classes.DecisionTreeClassifier))(1)	A sequence of data transformers with an optional final predictor. `Pipeline` allows you to sequentially apply a list of transformers to preprocess the data and, if desired, conclude the sequence with a final :term:`predictor` for predictive modeling. Intermediate steps of the pipeline must be 'transforms', that is, they must implement `fit` and `transform` methods. The final :term:`estimator` only needs to implement `fit`. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a `'__'`, as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to `'passthrough'` or `None`. For an example use case of `Pipeline` combined with :class:`~s...
sklearn.tree._classes.DecisionTreeClassifier(47)_ccp_alpha	0.0
sklearn.tree._classes.DecisionTreeClassifier(47)_class_weight	null
sklearn.tree._classes.DecisionTreeClassifier(47)_criterion	"gini"
sklearn.tree._classes.DecisionTreeClassifier(47)_max_depth	null
sklearn.tree._classes.DecisionTreeClassifier(47)_max_features	null
sklearn.tree._classes.DecisionTreeClassifier(47)_max_leaf_nodes	null
sklearn.tree._classes.DecisionTreeClassifier(47)_min_impurity_decrease	0.0
sklearn.tree._classes.DecisionTreeClassifier(47)_min_samples_leaf	1
sklearn.tree._classes.DecisionTreeClassifier(47)_min_samples_split	2
sklearn.tree._classes.DecisionTreeClassifier(47)_min_weight_fraction_leaf	0.0
sklearn.tree._classes.DecisionTreeClassifier(47)_monotonic_cst	null
sklearn.tree._classes.DecisionTreeClassifier(47)_random_state	33803
sklearn.tree._classes.DecisionTreeClassifier(47)_splitter	"best"
sklearn.pipeline.Pipeline(preprocessor=pairwise.padre.PDCDataTransformer,classifier=pairwise.padre.PairwiseDifferenceClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier))(1)_memory	null
sklearn.pipeline.Pipeline(preprocessor=pairwise.padre.PDCDataTransformer,classifier=pairwise.padre.PairwiseDifferenceClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier))(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "preprocessor", "step_name": "preprocessor"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "classifier", "step_name": "classifier"}}]
sklearn.pipeline.Pipeline(preprocessor=pairwise.padre.PDCDataTransformer,classifier=pairwise.padre.PairwiseDifferenceClassifier(estimator=sklearn.tree._classes.DecisionTreeClassifier))(1)_verbose	false
pairwise.padre.PDCDataTransformer(1)_nominal_features	["Address_bit_1", "Address_bit_2", "Bit_0", "Bit_1", "Bit_2", "Bit_3"]
pairwise.padre.PDCDataTransformer(1)_numeric_features	[]
pairwise.padre.PDCDataTransformer(1)_string_features	[]