decision_tree.pyi (480B)
1 from typing import Any, Optional 2 import numpy as np 3 4 class ELCClassifier: 5 def __init__(self, depth: int, combinations: int, threadCount: int, objectiveFunction: Optional[str] = None) -> None: ... 6 def fit(self, X: np.ndarray, samples: int, y: np.ndarray, features: int) -> None: ... 7 def predict(self, X: np.ndarray, samples: int, features: int) -> np.ndarray: ... 8 def getDot(self) -> str: ... 9 def getSplits(self) -> int: ... 10 #def __repr__(self) -> str: ...