rapidminer-anomalydetection | RapidMiner Extension for Anomaly Detection | Predictive Analytics library

by Markus-Go Java Version: v2.4.1 License: No License

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

kandi X-RAY | rapidminer-anomalydetection Summary

rapidminer-anomalydetection is a Java library typically used in Analytics, Predictive Analytics applications. rapidminer-anomalydetection has no vulnerabilities and it has low support. However rapidminer-anomalydetection has 22 bugs and it build file is not available. You can download it from GitHub.

RapidMiner Extension for Anomaly Detection

Support

Quality

Security

License

Reuse

Support

rapidminer-anomalydetection has a low active ecosystem.

It has 85 star(s) with 24 fork(s). There are 11 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 8 have been closed. On average issues are closed in 133 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of rapidminer-anomalydetection is v2.4.1

Quality

rapidminer-anomalydetection has 22 bugs (0 blocker, 6 critical, 12 major, 4 minor) and 564 code smells.

Security

rapidminer-anomalydetection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

rapidminer-anomalydetection code analysis shows 0 unresolved vulnerabilities.

There are 10 security hotspots that need review.

License

rapidminer-anomalydetection 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.

Reuse

rapidminer-anomalydetection releases are available to install and integrate.

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

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

rapidminer-anomalydetection saves you 3006 person hours of effort in developing the same functionality from scratch.

It has 6482 lines of code, 312 functions and 60 files.

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

Top functions reviewed by kandi - BETA

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

Performs the evaluation
Initializes the labels
Evaluate the roc points
Checks to see if the outlier class is smaller than the smallest class
Performs the minimization
Swap the elements of the matrix
Reconnect the gradient
Do the actual work
Initialize the anomaly score
Performs the actual work
Adjust the anomaly score
Performs the knn algorithm
Computes the optimization objective function
Performs the actual algorithm
Assign a number of large clusters to a list of clusters
Calculate rho
Selects the optimal iterations
Gets the parameterTypes attribute of the Gaussian kernel
Performs the PCA operation
Read a model from an Svm_model file
Saves model to disk
Check svm parameter
Gets the parameter types
Builds the DL4J network
Returns the parameter types
Initialize the rule set

Get all kandi verified functions for this library.

rapidminer-anomalydetection Key Features

No Key Features are available at this moment for rapidminer-anomalydetection.

rapidminer-anomalydetection Examples and Code Snippets

No Code Snippets are available at this moment for rapidminer-anomalydetection.

Community Discussions

Trending Discussions on rapidminer-anomalydetection

Python 3 - Load JSON data into my .csv -file

QUESTION

Python 3 - Load JSON data into my .csv -file

Asked 2018-Jan-08 at 17:15

I actually try to write JSON in a data.csv file. I tried following solution from stackoverflow: How do I write a Python dictionary to a csv file?

So I come up with these:

...

ANSWER

Answered 2018-Jan-06 at 18:25

Markus = {'data': {'user': {'name': 'Markus Goldstein',
                   'repositories': {'nodes': [{'forkCount': 0,
                                               'issues': {'totalCount': 0},
                                               'name': 'repache'},
                                              {'forkCount': 4,
                                               'issues': {'totalCount': 3},
                                               'name': 'nf-hishape'},
                                              {'forkCount': 4,
                                               'issues': {'totalCount': 7},
                                               'name': 'ip-countryside'},
                                              {'forkCount': 42,
                                               'issues': {'totalCount': 29},
                                               'name': 'bonesi'},
                                              {'forkCount': 13,
                                               'issues': {'totalCount': 3},
                                               'name': 'rapidminer-anomalydetection'},
                                              {'forkCount': 0,
                                               'issues': {'totalCount': 0},
                                               'name': 'rapidminer-studio'}]}}}}

with open('Markus.csv', 'w') as markus:
    print ('name,forkCount,issues', file=markus)
    for node in Markus['data']['user']['repositories']['nodes']:
        print ('{},{},{}'.format(node['name'], node['forkCount'], node['issues']['totalCount']), file=markus)

Source https://stackoverflow.com/questions/48130328

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

Vulnerabilities

No vulnerabilities reported

Install rapidminer-anomalydetection

In RapidMiner, go to Help→Updates and Extensions (Marketplace) and search for “anomaly detection” and click on “Install”, or. Copy the <a target="_blank" href="https://github.com/Markus-Go/rapidminer-anomalydetection/releases/latest">jar file</a> to the “lib/plugins” directory of RapidMiner.
In RapidMiner, go to Help→Updates and Extensions (Marketplace) and search for “anomaly detection” and click on “Install”, or
Copy the <a target="_blank" href="https://github.com/Markus-Go/rapidminer-anomalydetection/releases/latest">jar file</a> to the “lib/plugins” directory of RapidMiner

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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