Python RandomForest - 未知标签错误 [英] Python RandomForest - Unknown label Error

问题描述

我在使用 RandomForest 拟合函数时遇到问题

I have trouble using RandomForest fit function

这是我的训练集

         P1      Tp1           IrrPOA     Gz          Drz2
0        0.0     7.7           0.0       -1.4        -0.3
1        0.0     7.7           0.0       -1.4        -0.3
2        ...     ...           ...        ...         ...
3        49.4    7.5           0.0       -1.4        -0.3
4        47.4    7.5           0.0       -1.4        -0.3
... (10k rows)

由于所有其他变量，我想使用 sklearn.ensemble RandomForest 来预测 P1

I want to predict P1 thanks to all the other variables using sklearn.ensemble RandomForest

colsRes = ['P1']
X_train = train.drop(colsRes, axis = 1)
Y_train = pd.DataFrame(train[colsRes])
rf = RandomForestClassifier(n_estimators=100)
rf.fit(X_train, Y_train)

这是我得到的错误:

ValueError: Unknown label type: array([[  0. ],
       [  0. ],
       [  0. ],
       ..., 
       [ 49.4],
       [ 47.4],

我没有发现有关此标签错误的任何信息，我使用的是 Python 3.5.任何建议都会有很大帮助！

I did not find anything about this label error, I use Python 3.5. Any advice would be a great help !

推荐答案

当你将标签 (y) 数据传递给 rf.fit(X,y) 时，它期望 y 是一维列表.对 Panda 框架进行切片总是会产生一个 2D 列表.因此，在您的用例中引发了冲突.您需要将pandas DataFrame 提供的2D 列表按照fit 函数的预期转换为1D 列表.

When you are passing label (y) data to rf.fit(X,y), it expects y to be 1D list. Slicing the Panda frame always result in a 2D list. So, conflict raised in your use-case. You need to convert the 2D list provided by pandas DataFrame to a 1D list as expected by fit function.

先尝试使用一维列表:

Y_train = list(train.P1.values)

如果这不能解决问题，您可以尝试使用MultinomialNB错误:未知标签类型"中提到的解决方案:

If this does not solve the problem, you can try with solution mentioned in MultinomialNB error: "Unknown Label Type":

Y_train = np.asarray(train['P1'], dtype="|S6")

所以你的代码变成了，

colsRes = ['P1']
X_train = train.drop(colsRes, axis = 1)
Y_train = np.asarray(train['P1'], dtype="|S6")
rf = RandomForestClassifier(n_estimators=100)
rf.fit(X_train, Y_train)

这篇关于Python RandomForest - 未知标签错误的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！