随笔分类 - 2024年秋 / 每日博客
摘要：<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="wi
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摘要：<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="wi
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摘要：<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="wi
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摘要：<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="wi
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摘要：<!DOCTYPE html> <html lang="en"> <head> <meta charset="utf-8"> <meta http-equiv="X-UA-Compatible" content="IE=edge"> <meta name="viewport" content="wi
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摘要：using System; using System.Data; using System.Data.SqlClient; using System.Windows.Forms; namespace Database.Manipulation { /** * 数据库操作类，对数据库查询、更新、删除等
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摘要：namespace Database.MainForm { partial class Reset { /// <summary> /// Required designer variable. /// </summary> private System.ComponentModel.IContai
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摘要：namespace Database { partial class Manage { /// <summary> /// Required designer variable. /// </summary> private System.ComponentModel.IContainer comp
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摘要：namespace Database { partial class Login { /// <summary> /// 必需的设计器变量。 /// </summary> private System.ComponentModel.IContainer components = null; ///
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摘要：namespace Database.MainForm { partial class ChangePassword { /// <summary> /// Required designer variable. /// </summary> private System.ComponentMode
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摘要：1、 （1）候选类：用户、会议室、会议中心、会议、会议人数、会议时间、邮寄、电子邮件、开会人员、代表证、预订、系统 (2)系统类： ①用户： 系统的使用者，具有预订、修改、取消会议的行为。 ②会议中心： 系统的主要服务实体，负责管理所有会议和相关操作。 ③会议室： 提供会议场所资源，需具备容量、使用
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摘要：机器学习大作业 import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt from sklearn.model_selection import train_test_sp
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摘要：import numpy as np import pandas as pd from sklearn import datasets from sklearn.model_selection import train_test_split, cross_val_score, StratifiedK
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摘要：# 导入相关库 import numpy as np from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split, cross_val_score from sklearn.c
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摘要：# 导入必要的库 import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split, cross_val_score, StratifiedKFold from s
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摘要：import numpy as np from sklearn.model_selection import train_test_split, cross_val_score, StratifiedKFold from sklearn.svm import SVC from sklearn.dat
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摘要：# 导入必要的库 from sklearn import datasets from sklearn.model_selection import train_test_split, cross_val_score, StratifiedKFold from sklearn.svm import S
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