本文介绍了Sklearn随机森林回归器出错的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
当尝试使用如下所示的y数据拟合随机森林回归模型时:
When trying to fit a Random Forest Regressor model with y data that looks like this:
[ 0.00000000e+00 1.36094276e+02 4.46608221e+03 8.72660888e+03
1.31375786e+04 1.73580193e+04 2.29420671e+04 3.12216341e+04
4.11395711e+04 5.07972062e+04 6.14904935e+04 7.34275322e+04
7.87333933e+04 8.46302456e+04 9.71074959e+04 1.07146672e+05
1.17187952e+05 1.26953374e+05 1.37736003e+05 1.47239359e+05
1.53943242e+05 1.78806710e+05 1.92657725e+05 2.08912711e+05
2.22855152e+05 2.34532982e+05 2.41391255e+05 2.48699216e+05
2.62421197e+05 2.79544300e+05 2.95550971e+05 3.13524275e+05
3.23365158e+05 3.24069067e+05 3.24472999e+05 3.24804951e+05
X数据如下:
[ 735233.27082176 735234.27082176 735235.27082176 735236.27082176
735237.27082176 735238.27082176 735239.27082176 735240.27082176
735241.27082176 735242.27082176 735243.27082176 735244.27082176
735245.27082176 735246.27082176 735247.27082176 735248.27082176
使用以下代码:
regressor = RandomForestRegressor(n_estimators=150, min_samples_split=1)
rgr = regressor.fit(X,y)
我收到此错误:
ValueError: Number of labels=600 does not match number of samples=1
我认为我的一组值的格式错误，但是从文档中对我来说不太清楚.
I assume one of my sets of values is in the wrong format but its not too clear to me from the documentation.
推荐答案
X的形状应为[n_samples, n_features]，您可以将X转换为
The shape of X should be [n_samples, n_features], you can transform X by
X = X[:, None]
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