hcluster | Hierarchical Clustering Algorithms | Machine Learning library

by dedupeio Python Version: v0.3.9 License: Non-SPDX

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

kandi X-RAY | hcluster Summary

hcluster is a Python library typically used in Artificial Intelligence, Machine Learning applications. hcluster has no bugs, it has no vulnerabilities, it has build file available and it has high support. However hcluster has a Non-SPDX License. You can download it from GitHub.

This library provides Python functions for hierarchical clustering. Its features include. It is a fork of clustering and distance functions from the scipy that removes all the dependencies on scipy. It preserves the API of hcluster 0.2. Part of the Dedupe.io cloud service and open source toolset for de-duplicating and finding fuzzy matches in your data.

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Support

hcluster has a highly active ecosystem.

It has 31 star(s) with 21 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 12 have been closed. On average issues are closed in 134 days. There are 1 open pull requests and 0 closed requests.

It has a negative sentiment in the developer community.

The latest version of hcluster is v0.3.9

Quality

hcluster has 0 bugs and 0 code smells.

Security

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

hcluster code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

hcluster has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

hcluster releases are available to install and integrate.

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

hcluster saves you 1739 person hours of effort in developing the same functionality from scratch.

It has 3850 lines of code, 391 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Square transformation matrix X
Copy a
Returns a copy of a list of arrays
Convert X to double
Evaluate the predecessor tree
Recursively test for each node
True if the node is a leaf node
Convert a matrix into a tree
Calculate the centroid of the centroid
R Return the number of observations in a distance matrix
Verify that y is a valid distance matrix
Compute the linkage of the covariance matrix
Kulsinski correlation
Compute the difference between two arrays
Compute the complete complete linkage
Compute square form of a matrix X
Calculate the average similarity
Compute the weighted weighted linkage
Return the sum of two blocks
Return the distance between two vectors
R Weighted Weighted Distribution
Calculate the median median similarity

Get all kandi verified functions for this library.

hcluster Key Features

No Key Features are available at this moment for hcluster.

hcluster Examples and Code Snippets

No Code Snippets are available at this moment for hcluster.

Community Discussions

Trending Discussions on hcluster

Unsupervised clustering of demand into groups of hours

Find the number of clusters using clusGAP function in R

how to predict the cluster label of a new observation using a hierarchical clustering?

create a matrix by applying user defined function to a set of vectors

"error: command 'cl.exe' failed: No such file or directory" - Python Dedupe Installtion

How to save a scipy dendrogram as high resolution file?

TypeError: scatter() got multiple values for argument 'c'

Get K from ClusGap when clustering in R

ImportError: cannot import name _hierarchy or DLL load failed: %1 is not a valid Win32 application

How to reduce leaves length for fitting labels in R dendrogram?

QUESTION

Unsupervised clustering of demand into groups of hours

Asked 2021-Feb-02 at 14:58

I have the following DataFrame that contains for each hour the corresponding consumption of a product. I want to somehow group those hours based on similar demand but the grouping of the hours must be consecutive in order to make sense. For instance, a meaningful grouping of hours could be 10-12 but not (10-12, 2, 4-5).

...

ANSWER

Answered 2021-Feb-01 at 19:26

This is a very similar heuristic that tries to achieve what you want.

Essentially you just list down your demand in an array and find out the largest continuous subarray where the absolute value of difference of consecutive elements is within a threshold. You can vary your threshold to get desired output. Setting things up:

Source https://stackoverflow.com/questions/65805620

QUESTION

Find the number of clusters using clusGAP function in R

Asked 2021-Jan-22 at 23:19

Could you help me find the ideal number of clusters using the clusGap function? There is a similar example in this link: https://www.rdocumentation.org/packages/factoextra/versions/1.0.7/topics/fviz_nbclust

But I would like to do it for my case. My code is below:

...

ANSWER

Answered 2021-Jan-22 at 23:19

The issue here is that you have specified K.max as 100, however, you only have eight observations in your dataset. As noted in the clusGap documentation, K.max is the
the maximum number of clusters to consider, hence, in your case, K.max cannot be greater than seven.

It is unclear to me that clustering is appropriate on a dataset of such small size. Nevertheless, please see below a working implementation. I have modified the plot_clusgap function from the R/Bioconductor phyloseq package to visualize the results.

Source https://stackoverflow.com/questions/65799784

QUESTION

how to predict the cluster label of a new observation using a hierarchical clustering?

Asked 2020-Nov-01 at 18:10

I want to study a population of 47532 individuals with 16230 features. Thus I created a matrix with 16230 lines and 47532 columns

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ANSWER

Answered 2020-Nov-01 at 18:10

The answer is simple: you cannot. Hierarchical clustering is not designed to predict cluster labels for new observations. The reason why this is happening is because it just links data points according to their distances and it is not defining "regions" for each cluster.

There are two solutions for you at this stage I believe:

For new data points, find the nearest observation in your data set (using the same distance function as during the training) and assign the same cluster label. This requires a bit more coding, and obviously, it is a bit of a hack. But keep in mind that the results might not make a lot of sense as you will be extrapolating cluster labels using a different methodology than the training procedure.
Use another clustering algorithm! It seems like you are using hierarchical clustering when your use case does not match the model. KMeans could be a good choice, as it explicitly can assign new data points to the closest cluster.

Source https://stackoverflow.com/questions/64589016

QUESTION

create a matrix by applying user defined function to a set of vectors

Asked 2020-Jun-11 at 19:31

I have this function to measure the similarity of a pair of dictionaries.

...

ANSWER

Answered 2020-Jun-11 at 19:31

We can use outer

Source https://stackoverflow.com/questions/62331763

QUESTION

"error: command 'cl.exe' failed: No such file or directory" - Python Dedupe Installtion

Asked 2019-Nov-25 at 01:18

I am trying to install dedupe module and I am getting an error below,

error: command 'cl.exe' failed: No such file or directory

Failed building wheel for dedupe
Failed building wheel for dedupe-hcluster
Failed building wheel for affinegap
Failed building wheel for pylbfgs
Failed building wheel for pyhacrf-datamade

I found this link, that did not help me to resolve.

I am using Windows 10 , 64-bit, Python 3.5.4 :: Anaconda custom (64-bit).

I found the .whl file here, (dedupe-1.9.2-cp35-cp35m-manylinux1_x86_64.whl) downloaded it and tried to use pip install <>.whl and I got an error,

dedupe-1.9.2-cp35-cp35m-manylinux1_x86_64.whl is not a supported wheel on this platform.

Any ideas on how to resolve this issue?

...

ANSWER

Answered 2018-Jul-08 at 18:58

So, finally, after more research I successfully installed dedupe library. Just thought of posting my own answer if anyone might come across this issue.

In the beginning I only had Visual Studio Build Tools 2017 installed with Visual Studio 2015.

After posting the question I installed Visual Studio Community 2017 (2). And then tried use pip install dedupe still gave me errors like in this post.

Then according to the post, I upgraded the numpy =1.14 and tried pip install dedupe, it worked.

(I am not an expert python setup person, not sure how to explain other than this plain explanation)

Source https://stackoverflow.com/questions/51233854

QUESTION

How to save a scipy dendrogram as high resolution file?

Asked 2019-Oct-22 at 14:29

I have a matrix which has 600 different labels. Therefore, it is really big file; and I couldn't see these labels very well, when I created a figure to cluster my data. How should I create a high resolution file and save it?

I already tried below code.

...

ANSWER

Answered 2019-Oct-22 at 14:29

The problem is not with your resolution, but the size of the image (or the size of the lines). Since i do not know how to change the linewidth in the dendogram plot, i will just go with the straight forward solution to make a HUGE image.

Source https://stackoverflow.com/questions/58495420

QUESTION

TypeError: scatter() got multiple values for argument 'c'

Asked 2019-Apr-26 at 10:59

I am trying to do hierarchy clustering on my MFCC array 'signal_mfcc' which is an ndarray with dimensions of (198, 12). 198 audio frames/observation and 12 coefficients/dimensions?

I am using a random threshold of '250' with 'distance' for the criterion as shown below:

...

ANSWER

Answered 2019-Apr-26 at 10:59

From this SO Thread, you can see why you have this error.

Fom the Scatter documentation, c is the 2nd optional argument, and the 4th argument total. This error means that your unpacking on np.transpose(signal_mfcc) returns more than 4 items. And as you define c later on, it is defined twice and it cannot choose which one is correct.

Example :

Source https://stackoverflow.com/questions/55866041

QUESTION

Get K from ClusGap when clustering in R

Asked 2019-Apr-14 at 09:59

I want to use clusgap to estimate the number of clusters needed for a given data set. The problem is i cannot get the k value from clusgap although this library is recommended for the gap statistic.

Below is how im using clusgap:

...

ANSWER

Answered 2019-Apr-14 at 09:59

Incase anyone comes across this, here is how i did it:

Source https://stackoverflow.com/questions/55673441

QUESTION

ImportError: cannot import name _hierarchy or DLL load failed: %1 is not a valid Win32 application

Asked 2019-Feb-17 at 22:51

I've been working on a project in a Jupyter notebook, and wanted to use dedupe. Through anaconda, only dedupe-hcluster is available on a windows machine, so I installed that and attempted to import hcluster within the notebook, which gave this error:

"ImportError: DLL load failed: %1 is not a valid Win32 application."

From what I've read up on, this means that either Python is 32 bit whilst hcluster is 64 bit, or vice versa. It's not clear to me however how to fix this.

I then tried to convert the notebook into a Pycharm script so that I may use another version of dedupe, either dedupe, dedupe-hcluster or pandas-dedupe. I had issues installing pandas-dedupe, so went with the two former. Importing dedupe gives this error:

"ImportError: No module named _lowlevel"

and importing hcluster gives this error:

"ImportError: cannot import name _hierarchy"

I've done what feels like endless reading on all 3 of these issues and am no closer to solving any of them. Any suggestions on how to fix any of the above will be much appreciated.

...

ANSWER

Answered 2019-Feb-17 at 22:51

If you are using Anaconda and a Jupyter notebook, make sure your Anaconda environment is active in your notebook.

Source https://stackoverflow.com/questions/54526204

QUESTION

How to reduce leaves length for fitting labels in R dendrogram?

Asked 2018-Jul-20 at 12:57

I produced a cluster with hcluster. original dendogram.

For formatting purposes I used as.dendogram. When I did that my labels were cut of. vertical dendogram

Even more by the horizontal orientation. The one I need. horizontal dendogram

The problem does not seams to be in margins since (for the horizontal one) I used par(oma = c(0, 0, 0, 8) with not label effect. It only a reduced my margins but not give more room for labels names. How can I make sure that the plot shows the entire model names?

...

ANSWER

Answered 2018-Jul-20 at 12:57

You should probably change mar and not oma in par():

Source https://stackoverflow.com/questions/51442380

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

Vulnerabilities

No vulnerabilities reported

Install hcluster

You can download it from GitHub.
You can use hcluster 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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