作业解析-机器学习案例

目录

1. 作业题目 ………………………………………………………………

2. 作业目的……………………………………………………………….

3. 运行效果……………………………………………………………….

4. 实现过程……………………………………………………………….

5. 知识点巩固 …………………………………………………………..

6 知识拓展………………………………………………………………..

7 学习建议………………………………………………………………..

作业辅导解析

LAB_WORKSHEET_WEEK[作业标题]

4th April,2018[日期]

1.作业题目:[Assignment 上面随便复制一点]

Disclaimer: This set of homework applies SMOTE to a seriously imbalanced dataset with a large number of features and data points. SMOTE is essentially a time consuming method. You need to start doing this homework early, so that you have enough time to run SMOTE on the full dataset. 1. The LASSO and Boosting for Regression
  1. Download the Communities and Crime data1 from https://archive.ics.uci. edu/ml/datasets/Communities+and+Crime. Use the _rst 1495 rows of data as the training set and the rest as the test set.
  2. The data set has missing values. Use a data imputation technique to deal with the missing values in the data set. The data description mentions some features are nonpredictive.………

2.作业目的:[作业的目的 1-3 个点都可以]

1、 掌握机器学习基本算法

3.运行效果: [运行结果截图]

image

4.实现过程:[部分核心代码截图, 截图部分的代码 prefer 中英文

注释]

image

参考源码图 1.1

核心代码上图所示,本次作业主要通过以下步骤实现: 1、 调用 smote 算法生成数据,注意正负样本都需要

2、 调用机器学习算法进行训练,预测

5.知识点巩固:[相关知识点 1-3 点总结]

理解算法的内在逻辑,才能写好程序。

6.知识拓展:[拓展知识点 1-3 点总结]

理解基础的机器学习算法,掌握使用常用的机器学习库。

7.学习建议:[根据学习 IT 的经验,写 1-3 , prefer 3 个点]

1.多写代码,多推导算法公式。