# -*- coding: utf-8 -*- """ ############################################################################### # 作者:wanglei5205 # 邮箱:[email protected] # 代码:http://github.com/wanglei5205 # 博客:http://cnblogs.com/wanglei5205 # 目的:学习xgboost的plot_importance函数 # 官方API文档:http://xgboost.readthedocs.io/en/latest/python/python_api.html#module-xgboost.training ############################################################################### """ ### load module import matplotlib.pyplot as plt from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score from xgboost import XGBClassifier from xgboost import plot_importance ### load datasets digits = datasets.load_digits() ### data analysis print(digits.data.shape) print(digits.target.shape) ### data split x_train,x_test,y_train,y_test = train_test_split(digits.data, digits.target, test_size = 0.3, random_state = 33) model = XGBClassifier() model.fit(x_train,y_train) ### plot feature importance fig,ax = plt.subplots(figsize=(15,15)) plot_importance(model, height=0.5, ax=ax, max_num_features=64) plt.show() ### make prediction for test data y_pred = model.predict(x_test) ### model evaluate accuracy = accuracy_score(y_test,y_pred) print("accuarcy: %.2f%%" % (accuracy*100.0)) """ 95.0% """
原文地址:https://www.cnblogs.com/Allen-rg/p/9520285.html
时间: 2024-09-30 16:06:40