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The right tool for the job
Posted by:
Bananamaster
Date: February 14, 2015 01:51PM
Hey guys,
I have this idea of what I want to do, but I'm not to sure which tool to use job.
I have a dataset which basically describes my transactions. I have a lot of different attributes like if the sold good is used or new or how long I had it on storage or if it was a bike or a boat and many more. Additionally for each of these transactions I have my margin which is, in some unfortunate cases, negative. I now want to find out: Which attribute or combination of attributes share the transactions I lose money on. The perfect result would be a tree reading somewhat like this:
I loose 1000$ on all of my transactions. 1% of which is lost on boats, so that is not the problem. The rest of the 99% split in 15% loss on new goods, but 84% on used. The 15% in new split in 1%: storage time under 5 days and 14% storage time over or equal to 5 days, whereas the 84% on used goods split in 12% cars and 72% bicycles. And so on.
Not a very complicated algorithm if each attribute is a discrete and limited set.
Now, is there a tool that can help me do that? If so: Is that a standard function and do I only have to import my data and use a given function (if yes: What function do I use?) or to I have to build a function like this on my own using that tool?
If there is no such tool, I could write a program like that on my own, but I would prefer not having to do that.
Thanks guys
Lukas
I have this idea of what I want to do, but I'm not to sure which tool to use job.
I have a dataset which basically describes my transactions. I have a lot of different attributes like if the sold good is used or new or how long I had it on storage or if it was a bike or a boat and many more. Additionally for each of these transactions I have my margin which is, in some unfortunate cases, negative. I now want to find out: Which attribute or combination of attributes share the transactions I lose money on. The perfect result would be a tree reading somewhat like this:
I loose 1000$ on all of my transactions. 1% of which is lost on boats, so that is not the problem. The rest of the 99% split in 15% loss on new goods, but 84% on used. The 15% in new split in 1%: storage time under 5 days and 14% storage time over or equal to 5 days, whereas the 84% on used goods split in 12% cars and 72% bicycles. And so on.
Not a very complicated algorithm if each attribute is a discrete and limited set.
Now, is there a tool that can help me do that? If so: Is that a standard function and do I only have to import my data and use a given function (if yes: What function do I use?) or to I have to build a function like this on my own using that tool?
If there is no such tool, I could write a program like that on my own, but I would prefer not having to do that.
Thanks guys
Lukas