小编Siv*_*aji的帖子

R代码:

my.data <- mtcars[,c(1,3)] # Which has only two columns mpg, disp

lm(mpg~disp,data=my.data) #R Code for fitting a regression line

R输出:

Call:
  lm(formula = mpg ~ disp, data = my.data)

Coefficients:
  (Intercept)         disp  
     29.59985     -0.04122  

将R数据集写入磁盘文件

write.table(my.data,'~/Downloads/mtcars',sep=",",row.name=F,col.names=F) 

八度代码:

cd ~/Downloads
data=load('mtcars') # Using R dataset to fit the model
x=data(:,2)
y=data(:,1) 
cd ~/Dropbox/ML/mlclass-ex1-004/mlclass-ex1 %without any errors
xn=featureNormalize(x) # feature Normalizing with mean and std 
x1=[ones(length(x),1),xn]
theta=zeros(size(x1,2),1)
g=gradientDescent(x1,y,theta,alpha=.1,10000)

g的输出是:

g =
20.0906
-5.0277

如果你看一下inter的截距和系数; R输出和八度输出没有近似匹配.

有没有人知道这种差异来自哪里？哪一个是对的？