#StackBounty: #machine-learning #python #decision-trees #text-mining #unsupervised-learning Better approach to assign values to determi…

Bounty: 100

I am trying to assign different values for each sentences based on information about the presence of hashtags, upper case letters/words (e.g. HATE) and some others.

I created a data frame which includes some binary values (1 or 0):

Sentence           Upper case   Hashtags
I HATE migrants       1             0
I like cooking        0             0
#trump said he is ok  0             1
#blacklives SUPPORT   1             1  

I would like to assign a value based on the binary values above, if they are satisfied or not, for example:

- if Upper case = 1 and Hashtags = 1 then assign -10;
- if Upper case = 1 and Hashtags = 0 then assign -5;
- if Upper case = 0 and Hashtags = 1 then assign -5;
- if Upper case = 0 and Hashtags = 0 then assign 0;

This would be ok for a small number of requests and combinations, but with three variables to check, it would be a greater number of combination to consider manually!
Do you know if there is a way to take into account all these in an easy (and feasible) way?

Someone told me about using regression, but I have never used it before for similar task. The context is about fake tweets.

Get this bounty!!!

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