I'm new to machine learning programming and am working on an application which will calculate weights of the attributes to calculate the ETAT (Estimated Turn Around Time) of some tasks in workflow. The set of attributes is not fixed.
For example: ETAT will depend on-
- No of properties
- Experience level of resources and many more.
For each workflow entity there can by a set of these attributes, i.e. a single workflow may be like:
- Language - English
- No. of properties - 1200
- Experience level of resources - Expert
Language - Russian
No. of properties - 21000
Experience level of resources - Basic
Now for the above set of attributes, how can I design my machine learning algorithm? Any pointers will be highly useful.