Trees

Tree

tree.Tree()

Base Class for tree representation.

Methods:

Tree.get_attributes()	Returns the model attributes.
Tree.plot_tree([pic_path])	Draws the input tree.
Tree.predict(X)	Predicts using the BinaryTree model.
Tree.predict_proba(X)	Returns the model probabilities.
Tree.predict_proba_sql(X)	Returns the SQL code needed to deploy the model probabilities.
Tree.predict_sql(X)	Returns the SQL code needed to deploy the model.
Tree.set_attributes(**kwargs)	Sets the model attributes.
Tree.to_graphviz([feature_names, ...])	Returns the code for a Graphviz tree.

Attributes:

Tree.object_type

Must be overridden in child class

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Binary Tree Regressor

tree.BinaryTreeRegressor(children_left, ...)

InMemoryModel implementation of binary trees for regression.

Methods:

BinaryTreeRegressor.get_attributes()	Returns the model attributes.
BinaryTreeRegressor.plot_tree([pic_path])	Draws the input tree.
BinaryTreeRegressor.predict(X)	Predicts using the BinaryTree model.
BinaryTreeRegressor.predict_proba(X)	Returns the model probabilities.
BinaryTreeRegressor.predict_proba_sql(X)	Returns the SQL code needed to deploy the model probabilities.
BinaryTreeRegressor.predict_sql(X)	Returns the SQL code needed to deploy the model.
BinaryTreeRegressor.set_attributes(**kwargs)	Sets the model attributes.
BinaryTreeRegressor.to_graphviz([...])	Returns the code for a Graphviz tree.

Attributes:

BinaryTreeRegressor.object_type

Must be overridden in child class

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Binary Tree Classifier

tree.BinaryTreeClassifier(children_left, ...)

InMemoryModel implementation of binary trees for classification.

Methods:

BinaryTreeClassifier.get_attributes()	Returns the model attributes.
BinaryTreeClassifier.plot_tree([pic_path])	Draws the input tree.
BinaryTreeClassifier.predict(X)	Predicts using the BinaryTree model.
BinaryTreeClassifier.predict_proba(X)	Returns the model probabilities.
BinaryTreeClassifier.predict_proba_sql(X)	Returns the SQL code needed to deploy the model probabilities.
BinaryTreeClassifier.predict_sql(X)	Returns the SQL code needed to deploy the model.
BinaryTreeClassifier.set_attributes(**kwargs)	Sets the model attributes.
BinaryTreeClassifier.to_graphviz([...])	Returns the code for a Graphviz tree.

Attributes:

BinaryTreeClassifier.object_type

Must be overridden in child class

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Binary Tree Anomaly

tree.BinaryTreeAnomaly(children_left, ...[, psy])

InMemoryModel implementation of binary trees for anomaly detection.

Methods:

BinaryTreeAnomaly.get_attributes()	Returns the model attributes.
BinaryTreeAnomaly.plot_tree([pic_path])	Draws the input tree.
BinaryTreeAnomaly.predict(X)	Predicts using the BinaryTree model.
BinaryTreeAnomaly.predict_proba(X)	Returns the model probabilities.
BinaryTreeAnomaly.predict_proba_sql(X)	Returns the SQL code needed to deploy the model probabilities.
BinaryTreeAnomaly.predict_sql(X)	Returns the SQL code needed to deploy the model.
BinaryTreeAnomaly.set_attributes(**kwargs)	Sets the model attributes.
BinaryTreeAnomaly.to_graphviz([...])	Returns the code for a Graphviz tree.

Attributes:

BinaryTreeAnomaly.object_type

Must be overridden in child class

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Non-Binary Tree

tree.NonBinaryTree(tree[, classes])

InMemoryModel implementation of non-binary trees.

Methods:

NonBinaryTree.get_attributes()	Returns the model attributes.
NonBinaryTree.plot_tree([pic_path])	Draws the input tree.
NonBinaryTree.predict(X)	Predicts using the CHAID model.
NonBinaryTree.predict_proba(X)	Returns probabilities using the CHAID model.
NonBinaryTree.predict_proba_sql(X)	Returns the SQL code needed to deploy the model probabilities.
NonBinaryTree.predict_sql(X)	Returns the SQL code needed to deploy the model using its attributes.
NonBinaryTree.set_attributes(**kwargs)	Sets the model attributes.
NonBinaryTree.to_graphviz([classes_color, ...])	Returns the code for a Graphviz tree.

Attributes:

NonBinaryTree.object_type

Must be overridden in child class