sklearn.inspection.plot_partial_dependence 파라미터 정리

plot_partial_dependence

plot_partial_dependence은 1.0에서 더 이상 사용되지 않으며 1.2에서 제거됩니다. 대신 PartialDependenceDisplay.from_estimator를 사용하십시오.

from sklearn.inspection import plot_partial_dependence

 

plot_partial_dependence 파라미터

estimator = BaseEstimator

X = {array-like, dataframe} of shape (n_samples, n_features)

features = list of {int, str, pair of int, pair of str}

feature_names = array-like of shape (n_features,), dtype=str, default=None

target = int, default=None

response_method = {‘auto’, ‘predict_proba’, ‘decision_function’}, default=’auto’

n_cols = int, default=3

grid_resolution = int, default=100

percentiles = tuple of float, default=(0.05, 0.95)

method = str, default=’auto’

n_jobs = int, default=None

verbose = int, default=0

line_kw = dict, default=None

ice_lines_kw = dict, default=None
# ex) ice_lines_kw={"color": "tab:blue", "alpha": 0.5, "linewidth": 0.5}

pd_line_kw = dict, default=None
# ex) pd_line_kw={'color':'k'}

 

contour_kw = dict, default=None

ax = Matplotlib axes or array-like of Matplotlib axes, default=None

 

kind = {‘average’, ‘individual’, ‘both’}, default=’average’

subsample = float, int or None, default=1000

random_state = int, RandomState instance or None, default=None