Spectral-Clustering | Spectral Clustering in C | Machine Learning library

by fedelebron Shell Version: Current License: No License

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kandi X-RAY | Spectral-Clustering Summary

Spectral-Clustering is a Shell library typically used in Artificial Intelligence, Machine Learning, Neo4j applications. Spectral-Clustering has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This is a preliminary version of spectral clustering in C++. The idea is to create a weighted graph from the given datapoints, where the weight between two points is given by some similarity function. We then use properties of the eigenvectors of the graph's Laplacian to compute points that represent the data well, later to use k-means clustering on this.

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Spectral-Clustering has a low active ecosystem.

It has 13 star(s) with 6 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 2 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 Spectral-Clustering is current.

Quality

Spectral-Clustering has 0 bugs and 0 code smells.

Security

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

Spectral-Clustering code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

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

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

It has 11 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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Spectral-Clustering Key Features

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Spectral-Clustering Examples and Code Snippets

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Community Discussions

Trending Discussions on Spectral-Clustering

scikit-learn spectral clustering: unable to find NaN lurking in data

Spectral Clustering a graph in python

Python input for Spectral Clustering

QUESTION

scikit-learn spectral clustering: unable to find NaN lurking in data

Asked 2018-Nov-21 at 06:37

I'm running spectral coclustering on this dataset of Jeopardy questions, and there is this frustrating issue I'm facing with the data. Note that I'm only clustering all the values in the 'question' column.

There is apparently a "divide by zero" ValueError occurring when I run biclustering on the dataset.

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ANSWER

Answered 2018-Nov-19 at 01:13

Some strings sequence like e.g. 'down out' results in a zero return value from TfidfVectorizer(). That causes the errors starting with a divide by zero error, which results in inf values in the mtx sparse matrix and this causes the second error.

As a workaround to this problem to remove this sequences or remove the zero matrix elements from the mtx matrix after it created by TfidfVectorizer.fit_transform(), which a bit tricky because of the sparse matrix operation.

I made the second solution, as I didn't dived into the original tasks, as follows:

Source https://stackoverflow.com/questions/53358270

QUESTION

Spectral Clustering a graph in python

Asked 2018-Aug-18 at 14:12

I'd like to cluster a graph in python using spectral clustering.

Spectral clustering is a more general technique which can be applied not only to graphs, but also images, or any sort of data, however, it's considered an exceptional graph clustering technique. Sadly, I can't find examples of spectral clustering graphs in python online.

Scikit Learn has two spectral clustering methods documented: SpectralClustering and spectral_clustering which seem like they're not aliases.
Both of those methods mention that they could be used on graphs, but do not offer specific instructions. Neither does the user guide. I've asked for such an example from the developers, but they're overworked and haven't gotten to it.
A good network to document this against is the Karate Club Network. It's included as a method in networkx.

I'd love some direction in how to go about this. If someone can help me figure it out, I can add the documentation to scikit learn.

Notes:

A question much like this one has already been asked on this site.

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ANSWER

Answered 2017-Sep-16 at 22:44

Without much experience with Spectral-clustering and just going by the docs (skip to the end for the results!):

Code:

Source https://stackoverflow.com/questions/46258657

QUESTION

Python input for Spectral Clustering

Asked 2018-Jun-14 at 06:32

I am using the code from https://github.com/pin3da/spectral-clustering/blob/master/spectral/utils.py to spectrally cluster data in https://cs.joensuu.fi/sipu/datasets/s1.txt

May i know how I can change the code such that it can take in txt file as input? I have given the original code below for reference

Original code from GitHub

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ANSWER

Answered 2018-Jun-14 at 06:32

The code you show here just opens a given mat or h5 file. The path to the file (path) and the name of the data set within the file (db_name) are provided as arguments to the load_dot_mat function.

To load your txt file, we can create our own little load function:

Source https://stackoverflow.com/questions/50848880

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

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