Difference between Hybrid CF Model and Learning-to-Rank Model

[wenqinglim]

Hi,

I'm a little confused when looking at the examples in the documentation.
What is the difference between the Hybrid and Learning-to-Rank models implemented here?

From the documentation, a Hybrid model is defined by:

model = LightFM(loss='warp',
                item_alpha=ITEM_ALPHA,
                no_components=NUM_COMPONENTS)

A Learning-to-Rank model is defined by:

warp_model = LightFM(no_components=num_components,
                    loss='warp',
                    learning_schedule='adagrad',
                    max_sampled=100,
                    user_alpha=alpha,
                    item_alpha=alpha)

The default lightFM model is:

LightFM(no_components=10, k=5, n=10, learning_schedule=’adagrad’, 
loss=’logistic’, learning_rate=0.05, rho=0.95, epsilon=1e-06, item_alpha=0.0, 
user_alpha=0.0, max_sampled=10, random_state=None)

I'm having trouble seeing a difference between both models. Does LightFM differentiate between the Hybrid CF and Learning-to-Rank? How do I make sure the model that I'm creating is a Hybrid model or a Learning-to-Rank model?

Would appreciate any advice on this. Thank you!

[impaktor]

For me "learning to rank" is what you call the BPR and the WARP loss functions.

E.g. see:
https://www.ethanrosenthal.com/2016/11/07/implicit-mf-part-2/

I'm not sure what makes you think "learning to rank" and hybrid model would be disjunct.

[wenqinglim]

For me "learning to rank" is what you call the BPR and the WARP loss functions.

E.g. see:
https://www.ethanrosenthal.com/2016/11/07/implicit-mf-part-2/

I'm not sure what makes you think "learning to rank" and hybrid model would be disjunct.

Thank you for your reply!

Does this mean that as long as I specifyloss='bpr' or loss='warp' , it is a learning-to-rank model?

Also, just to clarify, is learning-to-rank a subset of CF and Hybrid models?

[maciejkula]

Learning-to-rank and CF/hybrid models are largely independent concepts. Both bpr and warp are ranking losses.

[wenqinglim]

Learning-to-rank and CF/hybrid models are largely independent concepts. Both bpr and warp are ranking losses.

Yes, that is what I thought! Could you explain how I could run a LTR and CF/Hybrid on LightFM? How do I make sure the model that I'm creating is a Hybrid model or a Learning-to-Rank model?

[maciejkula]

1. If use use the warp or bpr losses, your model is a learning-to-rank model.
2. If you have any features in your item or user feature matrices (other than the identity features per item/user), your model is a hybrid model.

[wenqinglim]

That seems very clear, but what if I'm using warp or bpr losses and also using additional user/item features? Is it still a Hybrid CF model?

[SimonCW]

I’m closing this issue because it has been inactive for a long time. If you still encounter the problem, please open a new issue.

Thank you!