KMeans-Clustering | simple K-Means Clustering model | Machine Learning library

by mahesh147 Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | KMeans-Clustering Summary

KMeans-Clustering is a Python library typically used in Artificial Intelligence, Machine Learning applications. KMeans-Clustering has no bugs, it has no vulnerabilities and it has low support. However KMeans-Clustering build file is not available. You can download it from GitHub.

A simple K-Means Clustering model implemented in python

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KMeans-Clustering has a low active ecosystem.

It has 11 star(s) with 20 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of KMeans-Clustering is current.

Quality

KMeans-Clustering has 0 bugs and 0 code smells.

Security

KMeans-Clustering has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

KMeans-Clustering code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

KMeans-Clustering does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

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KMeans-Clustering releases are not available. You will need to build from source code and install.

KMeans-Clustering has no build file. You will be need to create the build yourself to build the component from source.

It has 29 lines of code, 0 functions and 1 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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KMeans-Clustering Key Features

No Key Features are available at this moment for KMeans-Clustering.

KMeans-Clustering Examples and Code Snippets

No Code Snippets are available at this moment for KMeans-Clustering.

Community Discussions

Trending Discussions on KMeans-Clustering

How to install a Python package on Linux so that it is found by the already working PostgreSQL 13 plpython3u extension?

plot kmeans clustering on more than 2 dimensional data

Kmeans centers in a group_by and summarize pipe

Dockerized flexdashboard app won't run in localhost

QUESTION

How to install a Python package on Linux so that it is found by the already working PostgreSQL 13 plpython3u extension?

Asked 2021-Sep-05 at 14:44

Spin-off:

I have tried to catch the idea of “Module not found” when importing a Python package within a plpython3u procedure, I did not know how to use the accepted answer there to make it run on Linux. Normally, this here should be a duplicate, but if there is a difference with with MacOS in the used paths, it might be good for a new question.

Installation of PostgreSQL 13

I am on WSL2 (Ubuntu 20.04). I installed with the commands of the official PostgreSQL Downloads page from the PostgreSQL Apt Repository for Ubuntu.

...

ANSWER

Answered 2021-Sep-01 at 18:24

The issue is that this:

python3.8 -m pip install pandas

installs a package(pandas in this case) to the site-packages in the home directory of the user running the command, so:

/home/my_user/.local/lib/python3.8/site-packages

The plpython3u extension running in Postgres is looking for the package in the system wide site-packages. To get the package there you need to do:

sudo python3.8 -m pip install pandas

Source https://stackoverflow.com/questions/69013111

QUESTION

plot kmeans clustering on more than 2 dimensional data

Asked 2021-May-13 at 11:26

I have a dataset with 6 columns and after using KMEANs I need to visualize the plot after clustering. I have six clusters. how can I do it? this my Kmeans clustering code:

...

ANSWER

Answered 2021-May-12 at 18:20

scaled_features is a numpy array, you cannot index an array with a string. You need to convert it first to a dataframe with this:

Source https://stackoverflow.com/questions/67502519

QUESTION

Kmeans centers in a group_by and summarize pipe

Asked 2021-Mar-04 at 19:33

Trying to find the coordinates of K-means cluster centers on groups in a large data frame. One option is to brute-force loop through. But it'd be nice to figure out some tidy way of making it work. This previous Q&A wasn't clear. Any ideas? Here are some things I've tried, and a MCVE I made via reprex. Many thanks,

...

ANSWER

Answered 2021-Mar-04 at 19:33

Here is a slight modification of your Idea 1, with the help from the purrr package. The results are in the Center column as a list.

Source https://stackoverflow.com/questions/66479109

QUESTION

Dockerized flexdashboard app won't run in localhost

Asked 2020-Mar-18 at 13:27

I am attempting to create a Dockerized Flexdashboard app. I am able to run it locally, but not in the localhost. I can, however, run shiny apps just fine within the same docker image. Interestingly, the error message in the localhost says 'Not Found' for the Flexdashboard app which is different than when a page doesn't exist at all ('Page Not Found').

How can I Dockerize a Flexdashboard app?

MWE ...

ANSWER

Answered 2020-Mar-18 at 13:27

This is likely a result of a bug in the rmarkdown package being used in your image (rmoarkdown v. 1.18) and is related to this: https://github.com/rstudio/rmarkdown/issues/1731 and https://github.com/rstudio/rmarkdown/issues/1714. I'm guessing http://localhost:3838/kmeansflex/kmeans2.Rmd does indeed work.

Here's how you could test this. Make a shiny app in the apps folder to see what version of rmarkdown is being run. Make a folder in apps called 'rmarkdown'. Then put the following simple ui.R and server.R scripts in there to build a shiny app (we know shiny apps render for you) to determine what version of rmarkdown you have:

The ui.R script

Source https://stackoverflow.com/questions/60656707

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

Vulnerabilities

No vulnerabilities reported

Install KMeans-Clustering

You can download it from GitHub.
You can use KMeans-Clustering like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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