最近把之前没写完的一篇文章拿出来重新改，里面一张柱状图真是显得很low，
于是在浏览博客时发现了一张很惊艳的图
瞬间觉得柱状图low爆了，于是各种找方法，终于找到了shap库，pip install shap安排上
导入库
anaconda search -t shap
pip install --channel 链接
下载完成
import numpy as np
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.inspection import permutation_importance
import shap
from matplotlib import pyplot as plt
data = pd.read_csv("./new_data.csv")
X= data.loc[:,data.columns!='EGFR']
y=data.loc[:, "EGFR"]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=12)
rf = RandomForestRegressor(n_estimators=100)
rf.fit(X_train, y_train)
explainer = shap.TreeExplainer(rf)
shap_values = explainer.shap_values(X_test)
shap.summary_plot(shap_values, X_test)
结果
瞬间高大上
