在mutual_info_regression预装的n_neighbors=3中,此代码适用于n_neighbors=3。
selector = SelectKBest(mutual_info_regression, k='all').fit(X, y)n_neighbors=2在mutual_info_regression中的请求
不要使用变体:
selector = SelectKBest(mutual_info_regression, k='all').fit(X, y,**{'n_neighbors':2})
selector = SelectKBest(mutual_info_regression(**{'n_neighbors':2}), k='all').fit(X, y)
selector = SelectKBest(mutual_info_regression(n_neighbors=2), k='all').fit(X, y)
selector = SelectKBest(mutual_info_regression,n_neighbors=2, k='all').fit(X, y)
scoring = make_scorer(mutual_info_regression, greater_is_better=True, n_neighbors = 2)
selector = SelectKBest(scoring, k='all').fit(feat, targ)发布于 2020-12-29 15:18:38
您可以使用pythons partial函数创建一个具有非默认值的记分器:
from functools import partial
scorer_function = partial(mutual_info_regression, n_neighbors=2)
selector = SelectKBest(scorer_function, k='all').fit(X, y)https://stackoverflow.com/questions/65481705
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