# randu dataset, part 2

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In my last post I have plotted randu dataset to show that all its points lie on 15 parallel planes. But I was not fully satified with the solution and decided to show this numerically.**R snippets**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

It can be done in four steps:

- identifying four points lying on the same plane and finding its equation (we know that we have 15 planes so it is enough to check 15*3+1 points to find them);
- applying the equation to all points in randu dataset to divide them into 15 classes;
- veryfying that the classes separate points into 15 parallel planes;
- plotting the solution changing colors for points on different planes.

library

**(**rgl**)**library

**(**caTools**)**# STEP 1

all.combs

**<-**combs**(**1**:**46, 4**)**i

**<-**1**repeat**

**{**

model

**<-**lm**(**z**~**x**+**y, data**=**randu**[**all.combs**[**i,**]**,**])****if**

**(**summary

**(**model

**)$**r.squared

**>**0.99999

**)**

**{**

**break**

**}**

i

**<-**i**+**1**}**

# STEP 2

line.class

**<-**predict**(**model, randu**)****–**randu**$**zline.class

**<-**factor**(**round**(**line.class**)****+**10**)**# STEP 3

summary

**(**lm**(**z**~**x**+**y**+**line.class, data**=**randu**))**# STEP 4

with

**(**randu, plot3d**(**x, y, z, axes**=****FALSE**, col**=**line.class, xlab

**=**“”, ylab**=**“”, zlab**=**“”**))**rgl.viewpoint

**(**theta**=****–**3.8, phi**=**3.8, fov**=**0, zoom**=**0.7**)**At step three we can see that the model obtains perfect fit. The final figure is plotted below:

To

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