Comments (4)
from triplet_recommendations_keras.
And then would I throw away the known, negative ratings that are below that threshold?
from triplet_recommendations_keras.
from triplet_recommendations_keras.
Thanks! Any ideas for modeling them jointly? One thing I've tried is treating it as a multiclass problem with 6 classes (class 0 = no rating, class 1-5 correspond to ratings).
from triplet_recommendations_keras.
Related Issues (15)
- Fixing NaNs with built-in Sigmoid HOT 4
- Does not run with Keras 0.3.3 HOT 5
- Exception: ('Invalid merge mode:', 'join') HOT 5
- Why not control the nb_epoch within the fit function? HOT 1
- Doubt about margin_triplet_loss HOT 4
- Test set triplet sample HOT 1
- Item features as inputs for Item embedding HOT 1
- Both test loss and validation loss go to 0.5 HOT 6
- Loss and output functions are different. HOT 2
- Please,I have a problem with your function "bpr_triplet_loss"... HOT 1
- AttributeError: 'NoneType' object has no attribute 'inbound_nodes'
- Extract Embedding Model after training HOT 1
- Error in running triplet_movielens.py HOT 2
- Issues using items metadata HOT 1
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from triplet_recommendations_keras.