訂單將與logit.classes_
(類別_是擬合模型的屬性,它表示y中存在的唯一類)的返回值相同,並且大多數情況下它們將在字符串的情況下按字母順序排列。
爲了解釋它,我們上述標籤Y對邏輯迴歸的隨機數據集:
import numpy as np
from sklearn.linear_model import LogisticRegression
X = np.random.rand(45,5)
y = np.array(['GR3', 'GR4', 'SHH', 'GR3', 'GR4', 'SHH', 'GR4', 'SHH',
'GR4', 'WNT', 'GR3', 'GR4', 'GR3', 'SHH', 'SHH', 'GR3',
'GR4', 'SHH', 'GR4', 'GR3', 'SHH', 'GR3', 'SHH', 'GR4',
'SHH', 'GR3', 'GR4', 'GR4', 'SHH', 'GR4', 'SHH', 'GR4',
'GR3', 'GR3', 'WNT', 'SHH', 'GR4', 'SHH', 'SHH', 'GR3',
'WNT', 'GR3', 'GR4', 'GR3', 'SHH'], dtype=object)
lr = LogisticRegression()
lr.fit(X,y)
# This is what you want
lr.classes_
#Out:
# array(['GR3', 'GR4', 'SHH', 'WNT'], dtype=object)
lr.coef_
#Out:
# array of shape [n_classes, n_features]
所以在coef_
矩陣,行中的索引0表示「GR3」(第一中classes_
類陣列,1 =「GR4」等等。
希望它能幫助。
它會簡單地從指數0責令'n_classses-1'。你通過數字或字符串'y'?如果字符串那麼將使用LabelEncoder將其轉換爲數字形式。你能在這裏展示你的'y'嗎? –
字符串。標籤是:''GR3','GR4','SHH','GR3','GR4','SHH','GR4','SHH','GR4', 'WNT','GR3 '','GR4','GR3','SHH','SHH','GR3','GR4','SHH', 'GR4','GR3','SHH','GR3','SHH' ,'GR4','SHH','GR3','GR4', 'GR4','SHH','GR4','SHH','GR4','GR3','GR3','WNT', 'SHH', 'GR4','SHH','SHH','GR3','WNT','GR3','GR4','GR3','SHH'],dtype = object)類'0,1,2,3'。哪個對應哪個? –
有沒有辦法訪問LogisticRegression對象內的LabelEncoder對象? –