Question

我正在尝试使用scikit learn库计算Cohen的非数值值的kappa。有没有办法将标签数组[“快乐”，“悲伤”，“快乐”]转换为花车？

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)

现在我收到此错误：

ValueError: could not convert string to float: "HAPPINESS"

Answer 1

您需要使用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

0.578947368421

给出输出

android:clickable:true

SKLL和Kappa用于非数字值

1 个答案: