【发布时间】:2022-01-16 14:35:46
【问题描述】:
我有两个 numpy 数组
import numpy as np
temp_1 = np.array([['19.78018766'],
['19.72487359'],
['19.70280336'],
['19.69589641'],
['19.69746018']])
temp 2 = np.array([['43.8'],
['43.9'],
['44'],
['44.1'],
['44.2']])
我正在准备X = np.stack((temp_1,temp_2), axis=-1)
看起来像这样
X = [[['19.78018766' '43.8']]
[['19.72487359' '43.9']]
[['19.70280336' '44']]
[['19.69589641' '44.1']]
[['19.69746018' '44.2']]]
我还有另一个变量 Y,它也是一个 numpy 数组
Y = np.array([['28.78'],
['32.72'],
['15.70'],
['32.69'],
['55.69']])
我正在尝试运行 RandomforestRegressor 模型
在哪里
from sklearn.ensemble import RandomForestRegressor
clf = RandomForestRegressor()
clf.fit(X,Y)
但是,它给了我这个错误
ValueError: Found array with dim 3. Estimator expected <= 2.
【问题讨论】:
标签: python numpy scikit-learn random-forest