标签: scikit-survival

我很困惑如何解释scikit-survival中.predict拟合CoxnetSurvivalAnalysis模型的输出.我已经阅读了scikit-survival中的笔记本生存分析介绍和API参考,但无法找到解释.以下是导致我混淆的最小例子:

import pandas as pd
from sksurv.datasets import load_veterans_lung_cancer
from sksurv.linear_model import CoxnetSurvivalAnalysis

# load data
data_X, data_y = load_veterans_lung_cancer()

# one-hot-encode categorical columns in X
categorical_cols = ['Celltype', 'Prior_therapy', 'Treatment']

X = data_X.copy()
for c in categorical_cols:
    dummy_matrix = pd.get_dummies(X[c], prefix=c, drop_first=False)
    X = pd.concat([X, dummy_matrix], axis=1).drop(c, axis=1)

# display final X to fit Cox Elastic Net model on
del data_X
print(X.head(3))

所以这是进入模型的X:

   Age_in_years  Celltype  Karnofsky_score  Months_from_Diagnosis  \
0          69.0  squamous …