regressional data to classification

Question

Can anyone assist me on how i go about arranging data that i used as continous input,to data that goes through pair combos for binary output.ie

                     out         

3  5  9  19     11

4  6 7  12      23

3 3 4 6 7       2 

to something similar

3  5  9  19     1

4  6 7  12      0      etc

     

Answer 1

I have alot of data that has continuous outputs.
I just wanted to know how i go about permutating ever pair for classifcation.
Literally 200 000 cases.Too much to do manually.

Answer 2

Please explain what you are trying to do and why do you need to change data this way.

Are you trying to run data mining classification algorithm to predict continuous column? If so, you need to break the output column into ranges and predict what range will the value belong to. (e.g. 0-10, 10-20, 20-30, ... 90-100)

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Tatyana Yakushev [PredixionSoftware.com]

Answer 3

I do apologise for being very unclear.

Reflecting on my thread it looks lazy and disrespectful of forum protocol.

Ive been studying horse racing and other sport events with inputs ive put together.

I have many samples of input variables for individual horses,irrespective of horse field sizes.

Desired outputs being 1 for 1st, 2 for 2nd etc.Ive normalized the inputs and ran it through PCA.

Im not getting results i'd hoped for.Noisy data also cleansed to an extent.

So i would like to delve into individual race samples and have binary outputs for every paired combo of the horses to interprate the winning horses without having to manually do this.

Horse1        output      1st -   1

horse 2      output         4th   - 0

etc

I thought having thousands of horses would have rectified the race field bias.and the lenghts beaten offset.