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Algorithm for SVD based recommendation engine

0

$begingroup$

I am trying to build an SVD based recommendation engine for MovieLens database. After going through multiple online tutorials and resources I have understood how SVD works if a user-rating matrix is given as an input to it. I wish to use collaborative user based prediction here.

My goal :

Train the recommendation engine using the train set (say, 70% of the entire dataset) and then predict the recommendations for the test set. And finally, compute the error in my predictions.

My doubt:

1.What is the algorithm to use the train set to train the model and then use it for predicting in the test set ?

2.If I apply SVD on the train set, then how exactly do I use the output, i.e. the three matrices (U,sigma,Vt) on the test set?

machine-learning recommender-system training machine-learning-model matrix-factorisation

share

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

0

$begingroup$

I am trying to build an SVD based recommendation engine for MovieLens database. After going through multiple online tutorials and resources I have understood how SVD works if a user-rating matrix is given as an input to it. I wish to use collaborative user based prediction here.

My goal :

Train the recommendation engine using the train set (say, 70% of the entire dataset) and then predict the recommendations for the test set. And finally, compute the error in my predictions.

My doubt:

1.What is the algorithm to use the train set to train the model and then use it for predicting in the test set ?

2.If I apply SVD on the train set, then how exactly do I use the output, i.e. the three matrices (U,sigma,Vt) on the test set?

machine-learning recommender-system training machine-learning-model matrix-factorisation

share

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

add a comment | 

$begingroup$

I am trying to build an SVD based recommendation engine for MovieLens database. After going through multiple online tutorials and resources I have understood how SVD works if a user-rating matrix is given as an input to it. I wish to use collaborative user based prediction here.

My goal :

Train the recommendation engine using the train set (say, 70% of the entire dataset) and then predict the recommendations for the test set. And finally, compute the error in my predictions.

My doubt:

1.What is the algorithm to use the train set to train the model and then use it for predicting in the test set ?

2.If I apply SVD on the train set, then how exactly do I use the output, i.e. the three matrices (U,sigma,Vt) on the test set?

machine-learning recommender-system training machine-learning-model matrix-factorisation

share

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

$endgroup$

share

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

share

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1

New contributor

Abhishek Kaushik is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.

asked 4 mins ago

Abhishek KaushikAbhishek Kaushik

1