Is it possible to cluster from n columns to shares of categorical values with unsupervised learning?
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I want to use n columns from a relatively big data set with building age, the share of single-family homes (and much more) to predict the share of given energy technology in the respective city.
The thing is I don't have data on the exact share, but rather conditional statements such that a district heating grid is more likely not going to exists when the housing density is too low or that CHP systems are likely to come with a gas boiler as well.
I'm trying to get an insight of the used technology ratio from data without having any form of labelled data to work with.
Is this even possible and if so can you provide me with literature or a hint on what I should look at?
Obviously, the correlation of data I have might not even point to the technologies I am looking for.
Ps: The Data I am using is census data as well as literature data.
python classification unsupervised-learning prediction
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$begingroup$
I want to use n columns from a relatively big data set with building age, the share of single-family homes (and much more) to predict the share of given energy technology in the respective city.
The thing is I don't have data on the exact share, but rather conditional statements such that a district heating grid is more likely not going to exists when the housing density is too low or that CHP systems are likely to come with a gas boiler as well.
I'm trying to get an insight of the used technology ratio from data without having any form of labelled data to work with.
Is this even possible and if so can you provide me with literature or a hint on what I should look at?
Obviously, the correlation of data I have might not even point to the technologies I am looking for.
Ps: The Data I am using is census data as well as literature data.
python classification unsupervised-learning prediction
New contributor
Phil is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I want to use n columns from a relatively big data set with building age, the share of single-family homes (and much more) to predict the share of given energy technology in the respective city.
The thing is I don't have data on the exact share, but rather conditional statements such that a district heating grid is more likely not going to exists when the housing density is too low or that CHP systems are likely to come with a gas boiler as well.
I'm trying to get an insight of the used technology ratio from data without having any form of labelled data to work with.
Is this even possible and if so can you provide me with literature or a hint on what I should look at?
Obviously, the correlation of data I have might not even point to the technologies I am looking for.
Ps: The Data I am using is census data as well as literature data.
python classification unsupervised-learning prediction
New contributor
Phil is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I want to use n columns from a relatively big data set with building age, the share of single-family homes (and much more) to predict the share of given energy technology in the respective city.
The thing is I don't have data on the exact share, but rather conditional statements such that a district heating grid is more likely not going to exists when the housing density is too low or that CHP systems are likely to come with a gas boiler as well.
I'm trying to get an insight of the used technology ratio from data without having any form of labelled data to work with.
Is this even possible and if so can you provide me with literature or a hint on what I should look at?
Obviously, the correlation of data I have might not even point to the technologies I am looking for.
Ps: The Data I am using is census data as well as literature data.
python classification unsupervised-learning prediction
python classification unsupervised-learning prediction
New contributor
Phil is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Phil is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Phil is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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