《统计学习导论-基于R应用》第二章：统计学习（代码）
A = matrix(seq(1,16),4,4)
A
| 1 | 5 | 9 | 13 |
| 2 | 6 | 10 | 14 |
| 3 | 7 | 11 | 15 |
| 4 | 8 | 12 | 16 |
A[1,]
- 1
- 5
- 9
- 13
A[-c(1,3),]
| 2 | 6 | 10 | 14 |
| 4 | 8 | 12 | 16 |
dim(A)
- 4
- 4
1.数据读取、查看
getwd()
‘E:/机器学习与量化交易研究课题/统计学习导论-基于R应用/ISLR/data’
Auto = read.table("Auto.data")
fix(Auto)
Auto = read.table("Auto.data",header= T,na.strings="?")
fix(Auto)
dim(Auto)
- 397
- 9
Auto = read.csv("Auto.csv",header= T, na.strings="?")
fix(Auto)
dim(Auto)
- 397
- 9
Auto[1:5,]
| mpg | cylinders | displacement | horsepower | weight | acceleration | year | origin | name |
|---|---|---|---|---|---|---|---|---|
| 18 | 8 | 307 | 130 | 3504 | 12.0 | 70 | 1 | chevrolet chevelle malibu |
| 15 | 8 | 350 | 165 | 3693 | 11.5 | 70 | 1 | buick skylark 320 |
| 18 | 8 | 318 | 150 | 3436 | 11.0 | 70 | 1 | plymouth satellite |
| 16 | 8 | 304 | 150 | 3433 | 12.0 | 70 | 1 | amc rebel sst |
| 17 | 8 | 302 | 140 | 3449 | 10.5 | 70 | 1 | ford torino |
Auto = na.omit(Auto) # 剔除空行
dim(Auto)
- 392
- 9
names(Auto) # 查看变量名（列名/特征）
- 'mpg'
- 'cylinders'
- 'displacement'
- 'horsepower'
- 'weight'
- 'acceleration'
- 'year'
- 'origin'
- 'name'
plot(mpg,cylinders) # R 不会默认数据集，需要指定
Error in plot(mpg, cylinders): 找不到对象'mpg'
Traceback:
1. plot(mpg, cylinders)
# 指定方式一
plot(Auto$mpg,Auto$cylinders)
# 指定方式二
attach(Auto)
plot(mpg, cylinders)
The following objects are masked from Auto (pos = 3):
acceleration, cylinders, displacement, horsepower, mpg, name,
origin, weight, year
The following objects are masked from Auto (pos = 4):
acceleration, cylinders, displacement, horsepower, mpg, name,
origin, weight, year
The following objects are masked from Auto (pos = 5):
acceleration, cylinders, displacement, horsepower, mpg, name,
origin, weight, year
The following objects are masked from Auto (pos = 6):
acceleration, cylinders, displacement, horsepower, mpg, name,
origin, weight, year
箱线图
# 将定量变量转变为定性变量（虽然是数值，但是种类比较少）
cylinders = as.factor(cylinders)
# plot()绘制的是散点图，如果X轴输入是定性变量，自动转为箱线图
plot(cylinders,mpg)
plot(cylinders,mpg,col="red")
plot(cylinders,mpg,col="red", varwidth= T) # varwidth是一个逻辑值。 设置为true以绘制与样本大小成比例的框的宽度。
plot(cylinders,mpg,col="red", varwidth= T, horizontal=T)
plot(cylinders,mpg,col="red", varwidth= T, xlab= "cylinders", ylab= "MPG")
直方图
hist(mpg)
hist(mpg, col = 2)
hist(mpg, col= 2, breaks = 15) # 建议的分组组数，标量R不一定会用，如需精确breaks= seq(1,6,0.5)
两两绘图
pairs(Auto) # 数据集中两两变量绘制散点图
pairs(~mpg+displacement+horsepower,Auto) # 指定子集
显示图中某点的某些信息
plot(horsepower,mpg)
identify(horsepower,mpg,name)
描述统计量
summary(Auto)
mpg cylinders displacement horsepower weight
Min. : 9.00 Min. :3.000 Min. : 68.0 Min. : 46.0 Min. :1613
1st Qu.:17.00 1st Qu.:4.000 1st Qu.:105.0 1st Qu.: 75.0 1st Qu.:2225
Median :22.75 Median :4.000 Median :151.0 Median : 93.5 Median :2804
Mean :23.45 Mean :5.472 Mean :194.4 Mean :104.5 Mean :2978
3rd Qu.:29.00 3rd Qu.:8.000 3rd Qu.:275.8 3rd Qu.:126.0 3rd Qu.:3615
Max. :46.60 Max. :8.000 Max. :455.0 Max. :230.0 Max. :5140
acceleration year origin name
Min. : 8.00 Min. :70.00 Min. :1.000 amc matador : 5
1st Qu.:13.78 1st Qu.:73.00 1st Qu.:1.000 ford pinto : 5
Median :15.50 Median :76.00 Median :1.000 toyota corolla : 5
Mean :15.54 Mean :75.98 Mean :1.577 amc gremlin : 4
3rd Qu.:17.02 3rd Qu.:79.00 3rd Qu.:2.000 amc hornet : 4
Max. :24.80 Max. :82.00 Max. :3.000 chevrolet chevette: 4
(Other) :365
summary(mpg)
Min. 1st Qu. Median Mean 3rd Qu. Max.
9.00 17.00 22.75 23.45 29.00 46.60