mrchrisjohnson / logistic-mf Goto Github PK
View Code? Open in Web Editor NEWLogistic Matrix Factorization for Implicit Feedback Data. http://stanford.edu/~rezab/nips2014workshop/submits/logmat.pdf
License: Other
logistic-mf's People
Contributors
Stargazers
Watchers
Forkers
mindis venuktan xuanhan863 n1epan beifeizhou jamoque datascience102 fangzheng354 lenovor denisparra lanternying semanticbeeng taolian disc5 lucentcosmos tsho kmodi4 minghao2016 neuron1682 agangzz samdkanai guihui shubhampachori12110095 shreyasfadnavis stevenfengli paulodfreitas ambier fchal divyam02 fagan2888 kristophergeorge florianscheidl vishalbelsare yueyedeai lxreelogistic-mf's Issues
Can we use it in movie recommendation system.
Can we use it for movie recommendation system on basis of how many time user view movie page,watching status,rating and like.
If yes then can you give me datasets format
Model Validation Question
This isn't a code issue at all, just a question about the MPR validation you chose for this model (if there's a better place for this q let me know):
When you say you randomly sampled "full entries", does that mean you just removed 10% of the r_ui values? If so, what does that do to the user by item matrix needed for estimation? I'm imagining the training matrix looks like swiss cheese with the test entries as holes.
Memory-optimization
Hi Chris,
I was wondering if there could be a csr_matrix impl of observation_matrix as my matrix is way to big but sparse. I tried changing the source code but the following operations in method "deriv" is consuming a lot of memory.
A = np.dot(self.user_vectors, self.item_vectors.T)
A += self.user_biases
A += self.item_biases.T
A = np.exp(A)
A /= (A + self.ones)
A = (self.counts + self.ones) * A
Can you think of any alternate way of doing this?
Regards,
Akshay
Ranking model of logistic-MF
Hi,
According to the performance of logistic-mf, I think it would be interesting if we make a ranking version of implicit-mf. How do you think? Can we apply it based on Bayesian Personalized Ranking?
Thanks.
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.