sequence-based-recommendations | python library | Recommender System library

by rdevooght Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | sequence-based-recommendations Summary

sequence-based-recommendations is a Python library typically used in Artificial Intelligence, Recommender System applications. sequence-based-recommendations has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This python library includes multiple collaboraborative filtering algorithm that make use of the sequence of actions of the user: they not only use the fact that a user rated a certain item, but also that he rated before this other item or after that other one. Some standard algorithms that do not use sequence information are also present for easier comparison. All those algorithms aims to solve the "item recommendation" or "top-N recommendation" problem, which mean that they are not designed to predict ratings values, but only to predict which items are of interest for a given user.

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Quality

Security

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Support

sequence-based-recommendations has a low active ecosystem.

It has 331 star(s) with 131 fork(s). There are 25 watchers for this library.

It had no major release in the last 6 months.

There are 12 open issues and 5 have been closed. On average issues are closed in 34 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of sequence-based-recommendations is current.

Quality

sequence-based-recommendations has no bugs reported.

Security

sequence-based-recommendations has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

sequence-based-recommendations is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

sequence-based-recommendations releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed sequence-based-recommendations and discovered the below as its top functions. This is intended to give you an instant insight into sequence-based-recommendations implemented functionality, and help decide if they suit your requirements.

Train the network
Compute the pareto front
Compute the train function
Print training progress
Compute validation metrics
Compiles the test function
Train the model
Set the data format for training
Prints the progress of the training
Returns the pareto front of the given metrics
Split validation and test splits
Returns the filename for the model
Prepare inputs for RNN
Get the filename for the model
Run top k recommendations on the input sequence
Generate a sequence of sequences
Saves the index mapping
Compute the top k recommendations for the given sequence
Generate mini - batch mini batch
Prepare the input
Compute the test function
Return the predictor for the given method
Prepare inputs for training
Create a readme file
Prepare the input layer
Prepare the network
Prepare input
Add predictor command parser

Get all kandi verified functions for this library.

sequence-based-recommendations Key Features

No Key Features are available at this moment for sequence-based-recommendations.

sequence-based-recommendations Examples and Code Snippets

No Code Snippets are available at this moment for sequence-based-recommendations.

Community Discussions

Trending Discussions on sequence-based-recommendations

ModuleNotFoundError: No module named 'rnn_base'

QUESTION

ModuleNotFoundError: No module named 'rnn_base'

Asked 2019-Mar-26 at 20:23

I am trying to run this python code but I will get the following error:

...

ANSWER

Answered 2019-Mar-26 at 20:23

Add the following code to your python:

Source https://stackoverflow.com/questions/55364956

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install sequence-based-recommendations

The library has many dependencies: numpy/scipy, theano and lasagne for the neural networks, Gensim for word2vec and pandas for the data manipulation. Numpy, scipy and Theano can be sometimes difficult to install, and we recommend looking at Theano's installation tutorial: http://deeplearning.net/software/theano/install.html Gensim and pandas are easily installed with pip. Lasagne is also installed with pip but you have to specify the version >=0.2.dev1.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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