Add plot_feature_importances to _BaseOGBMModel

from typing import Any
from typing import List
from typing import Optional
from typing import Union

import lightgbm as lgb
import numpy as np
import pandas as pd

TWO_DIM_ARRAYLIKE_TYPE = Union[np.ndarray, pd.DataFrame]

class _VotingBooster(object):
    @property
    def feature_name(self) -> List[str]:
        return self.boosters[0].feature_name

    def __init__(
        self,
        boosters: List[lgb.Booster],
        weights: Optional[np.ndarray] = None
    ) -> None:
        self.boosters = boosters
        self.weights = weights

    def predict(
        self,
        X: TWO_DIM_ARRAYLIKE_TYPE,
        **kwargs: Any
    ) -> TWO_DIM_ARRAYLIKE_TYPE:
        results = []

        for b in self.boosters:
            result = b.predict(X, **kwargs)

            results.append(result)

        return np.average(results, axis=0, weights=self.weights)

    def feature_importance(self, **kwargs: Any) -> np.ndarray:
        results = []

        for b in self.boosters:
            result = b.feature_importance(**kwargs)

            results.append(result)

        return np.average(results, axis=0, weights=self.weights)
Y-oHr-N / OptGBM

Add plot_feature_importances to _BaseOGBMModel #10
