dotnet / dotnet/machinelearning
Complicated recommendation model with multiple optional custom weighted attributes
- Dominant language
- C#
- Stars
- 9.4k
- Forks
- 2k
- Avg merge
- 2d 20h
- Merged PRs (30d)
- 11
Description
### System information
- OS version/distro: Windows 11
- .NET Version: NET 6
### Issue
- **What did you try?**: tried to build a recommendation model with multiple optional custom weighted attributes
- **What happened?**: could not figure out how to apply custom attributes with weight
- **What did you expect?**: build a model with custom weighted attributes
### Use case
I would like to develop a recommendation system for cars (yes, vehicles), where user can specify what they are interested in most, less important and least important.
The importance would be described as:
- High: the weight value is 10
- Medium: the weight value is 6
- Low: the weight value is 3
And for every attribute of the car, a user is able specify the importance to them. Which means every attribute is optional. For those attributes that are not specified by the user, it would have default weight at `Medium`.
For example, a user specifies importance as below:
- price: high (more expensive, **lower** the score would be)
- horse power: high (bigger horse power, higher the score would be)
- seats: high (the system consider the number of seats as: the more the seats, the higher the score would be)
- 4WD: low (for those cars that are FWD/4WD, it has higher score)
- tank/fuel range: medium (longer the range, higher the score)
- etc.
- etc.
Now, to build such model, I would expect **somehow** we could provide user-specified weighted attributes into the model so the result would be user based.
Not really sure how to do so. Any thoughts?
Yours,
Wilson
Contributor guide
Assessment
This issue has not been assessed yet.