Snode
Oblique decision tree classifier based on SVM nodes Splitter class
- class Splitter.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
- clfSVC
Classifier used
- Xnp.ndarray
input dataset in train time (only in testing)
- ynp.ndarray
input labes in train time
- featuresnp.array
features used to compute hyperplane
- impurityfloat
impurity of the node
- titlestr
label describing the route to the node
- weightnp.ndarray, optional
weights applied to input dataset in train time, by default None
- scalerStandardScaler, optional
scaler used if any, by default None
- classmethod copy(node: Splitter.Snode) Splitter.Snode [source]
- get_down() Splitter.Snode [source]
- get_up() Splitter.Snode [source]