非数值的SKLL和Kappa

Question

我试图用scikit学习库计算非数值的Cohen kappa。有没有办法把一系列标签[“快乐”，“悲伤”，“快乐”]转换成浮动？在

from skll.metrics import kappa
y_true = ["HAPPINESS","OTHER","NONE","FEAR","NONE","NONE","NONE","ANGER"]
y_pred = ["HAPPINESS","NONE","NONE","FEAR","NONE","NONE","NONE","NONE"] 
kappa_val = kappa(y_true, y_pred)

现在我得到一个错误：

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Answer 1

您需要使用LabelEncoder

from sklearn import preprocessing
from sklearn.metrics import classification
import numpy as np
y_true = ["HAPPINESS","OTHER","NONE","FEAR","NONE","NONE","NONE","ANGER"]
y_pred = ["HAPPINESS","NONE","NONE","FEAR","NONE","NONE","NONE","NONE"] 
enc = preprocessing.LabelEncoder()
enc.fit(np.hstack((y_pred, y_true))) #have to give it all possible labels
kappa_val = classification.cohen_kappa_score(enc.transform(y_true), enc.transform(y_pred))
print kappa_val

它给出了输出

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