开发者学堂课程【大数据之 R 语言速成与实战：R实例——预测海藻数量之获取预测模型】学习笔记，与课程紧密联系，让用户快速学习知识。
课程地址：https://developer.aliyun.com/learning/course/363/detail/4346
R 实例——预测海藻数量之获取预测模型
内容介绍
一. 获取预测模型目标
一. 获取预测模型目标
获取预测模型目标是预测140个水样中7种海藻的出现频率,本案例中考虑海藻频率是数值型数据因此可以考虑进行回归分析-多元线性回模型。
多元线性回归模型是最常用的统计数据分析方法,该模型给出了一个有关目标变量与组解释变量关系的线性函数建立回归模型。
1、辅助变量2、模型诊断信息
In(of-oPo, datas)sawhfiteryolibrary(O)eadcaloae)* <- alose( NAs (algae),Iclean. algar < knnImwtat ontaloar, k-10)
961.00,0.0974,810,31.01980.00.00.01990,00.0.92000.00,0F.8hesd(clean, algae)witer seall tedi an 8.00spring 5nd11映din8.358.057.7501.288370000428.750autu sea11 bedian8.1011.440.0205.330346.667125.66spring seall median 8. 07 4.877,11 tedt am8.069.05535610.16215:126 winter saal1hih8.2513.165.7509.248430.000⊥8.250po chla al a a3 a4 a5 a6 A17).00050.00,00.0(.00.034.28.30.0555.730
1.31.47.64.81.96.70.0
2.118.015.63.353.61.90.00.00.09.797.58
010.59.22.97.50.0
7.54.11.055.6028.415.114.61.40.022.512.62.9
0515.63.353.61.90.00.00.09139.7001.43.141.01.90.01.40.01.49.58010,
59.22.97.50.07,54,11.055.6628.415.114,61.40.022.512.62.9Iaal g-n(al w+. datas lean algae, 1:12)sumary(ealCalltIe(formula al w., data clean. lgaeL, 1:12])esi加alsr10 Median37,293-11.9582.6237.17:62.465oefficients:Estimate std. Irror t value proItlIntercept)3909175323.6098201.6560,0994aseas sumner0.333513.9858690.0840,93332castine34885763.8403630.9080,)6484
3head(alga.e. atoaet-maTNA (aleae), Iclean, algae <-krnImpstat on(aleae, kaloclean,algaehead(clean, alowe)Inal 4- In(al , dtaeclean algae, 1: 121)
