Snode

class stree.Snode(clf: sklearn.svm._classes.SVC, X: numpy.ndarray, y: numpy.ndarray, features: numpy.array, impurity: float, title: str, weight: Optional[numpy.ndarray] = None, scaler: Optional[sklearn.preprocessing._data.StandardScaler] = None)[source]

Bases: object

Nodes of the tree that keeps the svm classifier and if testing the dataset assigned to it

classmethod copy(node: stree.Strees.Snode) → stree.Strees.Snode[source]
get_classifier() → sklearn.svm._classes.SVC[source]
get_down() → stree.Strees.Snode[source]
get_features() → numpy.array[source]
get_impurity() → float[source]
get_partition_column() → int[source]
get_title() → str[source]
get_up() → stree.Strees.Snode[source]
is_leaf() → bool[source]
make_predictor()[source]

Compute the class of the predictor and its belief based on the subdataset of the node only if it is a leaf

set_classifier(clf)[source]
set_down(son)[source]
set_features(features)[source]
set_impurity(impurity)[source]
set_partition_column(col: int)[source]
set_title(title)[source]
set_up(son)[source]