How do I choose training data set for job recommendation using linear regression model?

Question

I have two kind of profiles in database.one is candidate prodile,another is job profile posted by recruiter.

in both the profiles i have 3 common field say location,skill and experience

i know the algorithm but i am having problem in creating training data set where my input feature will be location,skill and salary chosen from candidate profile,but i am not getting how to choose output (relevant job profile).

as far as i know output can only be a single variable, then how to choose relevant job profile as a output in my training set

or should i choose some other method?another thought is clustering.

score 3 · Accepted Answer · answered Oct 18 '16 at 12:17

3

As I understand you want to predict job profile given candidate profile using some prediction algorithm.

Well, if you want to use regression you need to know some historical data -- which candidates were given which jobs, then you can create some model based on this historical data. If you don't have such training data you need some other algorithm. Say, you could set location,skill and experience as features in 3d and use clustering/nearest neighbors to find candidate profile closest to a job profile.

answered Oct 18 '16 at 12:17

borowis

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thanks mate. how can i put matching jobs in the output of training row – Anshuman Singh Oct 18 '16 at 12:26
if you don't have this mapping, you can't do that. you have to use some other algorithm – borowis Oct 18 '16 at 12:28

score 2 · Answer 2 · answered Oct 18 '16 at 12:19

You could look at "recommender systems", they can be an answer to your problem. Starting with a content based algorithm (you will have to find a way to automate the labels of the jobs, or manually do them), you can improve to an hybrid one by gathering which jobs your users were actually interested (and become an hybrid recommender)

How do I choose training data set for job recommendation using linear regression model?

2 Answers2