06 2021 档案

题目
摘要：01 — 概述 1.scikit-learn 是目前编程最常用的机器学习库。 2.通过 降维 把数据维度降低为2维或者3维，可以实现数据的可视化。 3.教材推荐采用 Anaconda 包管理工具来构建机器学习开发环境。 4.对回归问题，标签通常是 连续 型的。 5.我们教材将机器学习系统构建分为了4 阅读全文
posted @ 2021-06-20 17:02 笔记_y 阅读(1692) 评论(0) 推荐(0) 编辑
简答题
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210619213758743-822170948.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210619213807396-706433500.png) ![im 阅读全文
posted @ 2021-06-19 21:42 笔记_y 阅读(83) 评论(0) 推荐(0) 编辑
14-DBSCAN
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607090833060-1107770618.png)![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607090840841-1929194292.png)![im... 阅读全文
posted @ 2021-06-07 09:10 笔记_y 阅读(60) 评论(0) 推荐(0) 编辑
13-聚类评价
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607090355639-1259361201.png)![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607090403237-1074596423.png)![im... 阅读全文
posted @ 2021-06-07 09:08 笔记_y 阅读(40) 评论(0) 推荐(0) 编辑
12-聚类
摘要：K近邻法（knn）是一种基本的分类与回归方法。k-means是一种简单而有效的聚类方法。 knn 算法思路： 如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)的样本中的大多数属于某一个类别，则该样本也属于这个类别。 k近邻模型的三个基本要素： k值的选择：k值的选择会对结果产生重大影响。较 阅读全文
posted @ 2021-06-07 08:50 笔记_y 阅读(53) 评论(0) 推荐(0) 编辑
11-多项式回归、ridge回归
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607083644510-2129750790.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607083654064-1132171441.png) ![ 阅读全文
posted @ 2021-06-07 08:40 笔记_y 阅读(63) 评论(0) 推荐(0) 编辑
10-最优化
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607083055491-569650603.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210607083105607-1107459704.png) ![i 阅读全文
posted @ 2021-06-07 08:36 笔记_y 阅读(50) 评论(0) 推荐(0) 编辑
09-线性回归
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604141641671-490790345.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604141650292-435109680.png) ![im 阅读全文
posted @ 2021-06-04 14:25 笔记_y 阅读(57) 评论(0) 推荐(0) 编辑
08-决策树与随机森林
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604141222128-842743431.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604141231779-513490732.png) ![im 阅读全文
posted @ 2021-06-04 14:16 笔记_y 阅读(62) 评论(0) 推荐(0) 编辑
07-朴素贝叶斯
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604140321826-1460402417.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210604140333248-1994342429.png) ![ 阅读全文
posted @ 2021-06-04 14:09 笔记_y 阅读(56) 评论(0) 推荐(0) 编辑
06-SVM
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603233528662-1650222473.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603233542438-1847883726.png) ![ 阅读全文
posted @ 2021-06-03 23:38 笔记_y 阅读(54) 评论(0) 推荐(0) 编辑
05-逻辑回归
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603233051812-978053492.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603233100827-693626070.png) ![im 阅读全文
posted @ 2021-06-03 23:35 笔记_y 阅读(63) 评论(0) 推荐(0) 编辑
04-数据集划分与学习曲线
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603232839728-1044399009.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603232848547-1854780506.png) ![ 阅读全文
posted @ 2021-06-03 23:30 笔记_y 阅读(68) 评论(0) 推荐(0) 编辑
03-分类评价指标
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603232503154-460659691.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603232516041-124974455.png) ![im 阅读全文
posted @ 2021-06-03 23:27 笔记_y 阅读(55) 评论(0) 推荐(0) 编辑
02-KNN分类
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603231739821-40736722.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603232148119-41963611.png) ![imag 阅读全文
posted @ 2021-06-03 23:23 笔记_y 阅读(57) 评论(0) 推荐(0) 编辑
01-绪论
摘要：![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603231246805-1374716607.png) ![image](https://img2020.cnblogs.com/blog/2380476/202106/2380476-20210603231303946-1130050892.png) ![ 阅读全文
posted @ 2021-06-03 23:17 笔记_y 阅读(51) 评论(0) 推荐(0) 编辑