movielens | Promise based Node API for the movielens unpublished API | REST library

by longseespace JavaScript Version: Current License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | movielens Summary

movielens is a JavaScript library typically used in Web Services, REST, Nodejs applications. movielens has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can install using 'npm i movielens' or download it from GitHub, npm.

Promise based Node API for the movielens unpublished API.

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Quality

Security

License

Reuse

Support

movielens has a low active ecosystem.

It has 6 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of movielens is current.

Quality

movielens has no bugs reported.

Security

movielens has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

movielens 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

movielens releases are not available. You will need to build from source code and install.

Deployable package is available in npm.

Installation instructions are not available. Examples and code snippets are available.

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movielens Key Features

No Key Features are available at this moment for movielens.

movielens Examples and Code Snippets

Start a standard TensorFlow server .

python

Lines of Code : 71

License : Non-SPDX (Apache License 2.0)

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def run_standard_tensorflow_server(session_config=None):
  """Starts a standard TensorFlow server.

  This method parses configurations from "TF_CONFIG" environment variable and
  starts a TensorFlow server. The "TF_CONFIG" is typically a json string

Runs the server .

python

Lines of Code : 67

License : Non-SPDX (Apache License 2.0)

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def _run_std_server(cluster_spec=None,
                    task_type=None,
                    task_id=None,
                    session_config=None,
                    rpc_layer=None,
                    environment=None):
  """Runs a standard serv

Stop the server .

python

Lines of Code : 28

License : Non-SPDX (Apache License 2.0)

Copy

def stop_server(self, grace=1.0):
    """Request server stopping.

    Once stopped, server cannot be stopped or started again. This method is
    non-blocking. Call `wait()` on the returned event to block until the server
    has completely stopped.

Community Discussions

Trending Discussions on movielens

How can I ensure that all users and all items appear in the training set of my recommender system?

LensKit Recommender only returns results for some users, otherwise returns empty DataFrame. Why is this happening?

issue with calculating accuracy

Database creation takes to long in neo4j

How would I prepare a table of the top 15 movies using their names and average ratings?

Checking file checksum in Python

Pandas dataframe convert multiple rows and columns to single row[key] and column[key]

How to select string DataFrame using contains?

Join two tables in different databases with setting limit MySQL

HiveQL query for data marked as table column names

QUESTION

How can I ensure that all users and all items appear in the training set of my recommender system?

Asked 2021-Jun-11 at 20:37

I am building a recommender system in Python using the MovieLens dataset (https://grouplens.org/datasets/movielens/latest/). In order for my system to work correctly, I need all the users and all the items to appear in the training set. However, I have not found a way to do that yet. I tried using sklearn.model_selection.train_test_split on the partition of the dataset relevant to each user and then concatenated the results, thus succeeding in creating training and test datasets that contain at least one rating given by each user. What I need now is to find a way to create training and test datasets that also contain at least one rating for each movie.

...

ANSWER

Answered 2021-Jun-11 at 20:37

This requirement is quite reasonable, but is not supported by the data ingestion routines for any framework I know. Most training paradigms presume that your data set is populated sufficiently that there is a negligible chance of missing any one input or output.

Since you need to guarantee this, you need to switch to an algorithmic solution, rather than a probabilistic one. I suggest that you tag each observation with the input and output, and then apply the "set coverage problem" to the data set.

You can continue with as many distinct covering sets as needed to populate your training set (which I recommend). Alternately, you can set a lower threshold of requirement -- say get three sets of total coverage -- and then revert to random methods for the remainder.

Source https://stackoverflow.com/questions/67942944

QUESTION

LensKit Recommender only returns results for some users, otherwise returns empty DataFrame. Why is this happening?

Asked 2021-May-23 at 02:53

I am trying to implement a group recommender system with the Django framework, using the LensKit tools for Python (specifically a Recommender object which adapts the UserUser algorithm). However, it only returns individual recommendations in some cases (for some specific users), but it always returns recommendations for groups of users (I create a hybrid user whose scores are the average of group members' scores and request recommendations for it). Below is my implementation for requesting recommendations for an individual user, as well as for a group:

...

ANSWER

Answered 2021-May-23 at 02:53

The most likely cause of this problem is that the user-user recommender cannot build enough viable neighborhoods to provide recommendations. This is a downside to neighborhood-based recommendations.

The solutions are to either switch to an algorithm that can always recommend for a user with some ratings (e.g. one of the matrix factorization algorithms), and/or use a fallback algorithm such as Popular to recommend when the personalized collaborative filter cannot recommend.

(Another solution would be to implement one of the various cold-start recommenders or a content-based recommender for LensKit, but none are currently provided by the project.)

Source https://stackoverflow.com/questions/67647854

QUESTION

issue with calculating accuracy

Asked 2021-May-05 at 17:27

i'm using Torch Metrics to try to calculate the accuracy of my model. But i'm getting this error. I tried using .to(device="cuda:0") but I got a cuda initialization error. I also tried using .cuda() but that didn't work either. I'm using PyTorch lightning with a Titan Xp GPU. Im using a mish activation function with the Movie-lens data set.

code:

...

ANSWER

Answered 2021-May-05 at 17:27

I am explaining it here,

This command:

Source https://stackoverflow.com/questions/67393293

QUESTION

Database creation takes to long in neo4j

Asked 2021-Apr-12 at 18:25

Updated question:

I'm new in neo4j and im trying to create a movie rating database. I have a file with 100.000 registers (2,3 MB) that represents when a user rated a movie; the file look like this (this dataset is from MovieLens):

dataset file

I'm using py2neo and I create de datebase with this code:

...

ANSWER

Answered 2021-Apr-12 at 03:57

You are starting with a CSV file, right? You could use LOAD CSV to bring it into Neo4j. Use your python code to put the csv in the Neo4j Import directory. Then run this query ...

Source https://stackoverflow.com/questions/67051613

QUESTION

How would I prepare a table of the top 15 movies using their names and average ratings?

Asked 2021-Apr-05 at 06:02

Before reading this I am extremely new to coding so many things I am going to ask are cringe.

I am using http://www.d2l.ai/chapter_recommender-systems/movielens.html and trying to use that dataset to grow my coding skills. I am coding in Python's Spyder.

What I was wondering was what if I was the CEO and wanted to know what the top 15 movies were by Name and Ratings given by users. This is simple enough for an intermediate coder but mind you I am the lowest a beginner can be. The code I have used so far is copy paste what they have done on that link in order to upload the file into Python.

My Mindset: I believe my next steps would be to create a DataFrame using Pandas and somehow use a value count. I am searching things up online and its throwing a bunch of info at me like Jaccard Similarities and Distances. I don't know if this type of question requires such a setup.

Any Help would be loved and if you do respond I may ask more questions out of curiosity.

...

ANSWER

Answered 2021-Apr-05 at 06:02

Assume you have downloaded ml-100k.zip and store it somewhere.

Source https://stackoverflow.com/questions/66948298

QUESTION

Checking file checksum in Python

Asked 2021-Apr-02 at 21:03

I have to write in Python that performs the following tasks:

1- Download the Movielens datasets from the url ‘http://files.grouplens.org/datasets/movielens/ml- 25m.zip’
2- Download the Movielens checksum from the url ‘http://files.grouplens.org/datasets/movielens/ml- 25m.zip.md5’
3- Check whether the checksum of the archive corresponds to the downloaded one
4- In case of positive check, print the names of the files contained by the downloaded archive

This is what I wrote up to now:

...

ANSWER

Answered 2021-Apr-02 at 20:50

Your code isn't actually making any of the requests.

Source https://stackoverflow.com/questions/66925001

QUESTION

Pandas dataframe convert multiple rows and columns to single row[key] and column[key]

Asked 2021-Mar-19 at 17:00

I have a pandas dataframe that I need to convert to a movielens type with User ID, MovieId, Rating. The dataframe I have is in a dense form

...

ANSWER

Answered 2021-Mar-19 at 16:25

Try with melt then sort_values

Source https://stackoverflow.com/questions/66711913

QUESTION

How to select string DataFrame using contains?

Asked 2021-Feb-15 at 22:30

Using spark 2.0, I want to process the Full MovieLens Dataset.

my dataframe contains information about movies :

...

ANSWER

Answered 2021-Feb-15 at 21:34

You can filter it:

Source https://stackoverflow.com/questions/66197858

QUESTION

Join two tables in different databases with setting limit MySQL

Asked 2021-Feb-08 at 20:17

How can I set limit for inner join two tables in different databases?

...

ANSWER

Answered 2021-Feb-08 at 20:17

You can read about LIMIT HERE

You can also read about ORDER BY HERE

The syntax for them based on the SQL you posted would be:

Source https://stackoverflow.com/questions/66108491

QUESTION

HiveQL query for data marked as table column names

Asked 2020-Dec-30 at 19:16

I work in HDP 2.6.5 platformon using Hive (1.2.1000.2.6.5.0-292) on a simple database based on data from: https://grouplens.org/datasets/movielens/100k/
I have 4 tables named: genre, movies, ratings, users as below:

...

ANSWER

Answered 2020-Dec-30 at 12:33

Awful data model. You should have a table with one row per movie and genre.

To solve this problem, I would suggest unpivoting to aggregate:

Source https://stackoverflow.com/questions/65506844

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

Vulnerabilities

No vulnerabilities reported

Install movielens

You can install using 'npm i movielens' or download it from GitHub, npm.

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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