FrequentSubgraphMining | python implementation of the Gaston frequent subgraph | Data Mining library

 by   ColinConduff Python Version: Current License: No License

kandi X-RAY | FrequentSubgraphMining Summary

kandi X-RAY | FrequentSubgraphMining Summary

FrequentSubgraphMining is a Python library typically used in Data Processing, Data Mining applications. FrequentSubgraphMining has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Gaston Graph Mining with Python This is a python implementation of the Gaston graph mining algorithm. "Gaston finds all frequent subgraphs by using a level-wise approach in which first simple paths are considered, then more complex trees and finally the most complex cyclic graphs. It appears that in practice most frequent graphs are not actually very complex structures; Gaston uses this quickstart observation to organize the search space efficiently. To determine the frequency of graphs, Gaston employs an occurrence list based approach in which all occurrences of a small set of graphs are stored in main memory.". Installation: cd gaston_py pip install . Command Line Interface: For usage instructions, use the following command. gaston -h. Examples: gaston 0.95 test_files/medium_chemical.txt -o output_files/ -c -t gaston 6 test_files/medium_chemical.txt gaston 2 test_files/Chemical_340.txt. Run Tests: python setup.py test. References: [1] Siegfried Nijssen and Joost Kok. A Quickstart in Frequent Structure Mining Can Make a Difference. Proceedings of the SIGKDD, 2004. Additional Resources: Java implementation of the Gaston algorithm
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              FrequentSubgraphMining has a low active ecosystem.
              It has 11 star(s) with 6 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. On average issues are closed in 378 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of FrequentSubgraphMining is current.

            kandi-Quality Quality

              FrequentSubgraphMining has 0 bugs and 0 code smells.

            kandi-Security Security

              FrequentSubgraphMining has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              FrequentSubgraphMining code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              FrequentSubgraphMining does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              FrequentSubgraphMining releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              It has 604 lines of code, 66 functions and 19 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed FrequentSubgraphMining and discovered the below as its top functions. This is intended to give you an instant insight into FrequentSubgraphMining implemented functionality, and help decide if they suit your requirements.
            • Finds a set of subgraphs
            • Iterate through the given fragments
            • Return whether the embedding is frequent
            • Return True if the fragment is not already visited
            • Create a embedding list based on source label
            • Yield the edge labels for the given node
            • Create embedding list
            • Computes the embedded embedding list
            • Apply a refinement to a graph
            • Create a cycle between two fragments
            • Creates a new embedding
            • Append new edge to the given path
            • Computes the symmetrized symmetry
            • Compute the symmetry of an embedding list
            Get all kandi verified functions for this library.

            FrequentSubgraphMining Key Features

            No Key Features are available at this moment for FrequentSubgraphMining.

            FrequentSubgraphMining Examples and Code Snippets

            No Code Snippets are available at this moment for FrequentSubgraphMining.

            Community Discussions

            QUESTION

            different tree for the same data set
            Asked 2022-Feb-21 at 19:57

            I am working on Pima Indians Diabetes Database in Weka. I noticed that for decision tree J48 the tree is smaller as compared to the Random Tree. I am unable to understand why it is like this? Thank you.

            ...

            ANSWER

            Answered 2022-Feb-21 at 19:57

            Though they both are decision trees, they employ different algorithms for constructing the tree, which will (most likely) give you a different outcome:

            • J48 prunes the tree by default after it built its tree (Wikipedia).
            • RandomTree (when using default parameters) inspects a maximum of log2(num_attributes) attributes for generating splits.

            Source https://stackoverflow.com/questions/71201615

            QUESTION

            Remove duplicates from a tuple
            Asked 2022-Feb-09 at 23:43

            I tried to extract keywords from a text. By using "en_core_sci_lg" model, I got a tuple type of phrases/words with some duplicates which I tried to remove from it. I tried deduplicate function for list and tuple, I only got fail. Can anyone help? I really appreciate it.

            ...

            ANSWER

            Answered 2022-Feb-09 at 22:08

            doc.ents is not a list of strings. It is a list of Span objects. When you print one, it prints its contents, but they are indeed individual objects, which is why set doesn't see they are duplicates. The clue to that is there are no quote marks in your print statement. If those were strings, you'd see quotation marks.

            You should try using doc.words instead of doc.ents. If that doesn't work for you, for some reason, you can do:

            Source https://stackoverflow.com/questions/71057313

            QUESTION

            Can't get value of tag using BeautifulSoup
            Asked 2022-Jan-22 at 22:36

            my code:

            ...

            ANSWER

            Answered 2022-Jan-11 at 13:11

            Note: In new code use find_all() instead of old findAll() syntax - your html looks not valid

            Source https://stackoverflow.com/questions/70666777

            QUESTION

            The website has 9 pages and my code just add the last page elements to the list
            Asked 2022-Jan-12 at 01:42

            The website has 9 pages and my code just add the last page elements to the list. I want to add all elements for all pages next together in list.

            ...

            ANSWER

            Answered 2022-Jan-10 at 08:27
            What happens?

            Code works well, but iterates to fast and elements your looking for are not present in the moment you try to find them.

            How to fix?

            Use selenium waits to check if elements are present in the DOM:

            Source https://stackoverflow.com/questions/70647571

            QUESTION

            Compare two dataframes column values. Find which values are in one df and not the other
            Asked 2021-Nov-07 at 19:24

            I have the following dataset

            ...

            ANSWER

            Answered 2021-Nov-07 at 19:11

            You could just use normal sets to get unique customer ids for each year and then subtract them appropriately:

            Source https://stackoverflow.com/questions/69875643

            QUESTION

            Pandas : Linear Regression apply standard scaler to some columns
            Asked 2021-Nov-06 at 11:48

            So I have the following dataset :

            ...

            ANSWER

            Answered 2021-Nov-06 at 11:46

            You can split your data frame like this:

            Source https://stackoverflow.com/questions/69863485

            QUESTION

            How can I use SVM classifier to detect outliers in percentage changes?
            Asked 2021-Nov-04 at 09:28

            I have a pandas dataframe that is in the following format:

            This contains the % change in stock prices each day for 3 companies MSFT, F and BAC.

            I would like to use a OneClassSVM calculator to detect whether the data is an outlier or not. I have tried the following code, which I believe detects the rows which contain outliers.

            ...

            ANSWER

            Answered 2021-Nov-04 at 09:28

            It's not very clear what is delta and df in your code. I am assuming they are the same data frame.

            You can use the result from svm.predict , here we leave it as blank '' if not outlier:

            Source https://stackoverflow.com/questions/69836604

            QUESTION

            How can I change the order of the attributes in Weka?
            Asked 2021-Oct-08 at 00:07

            I was doing a machine learning task in Weka and the dataset has 486 attributes. So, I wanted to do attribute selection using chi-square and it provides me ranked attributes like below:

            Now, I also have a testing dataset and I have to make it compatible. But how can I reorder the test attributes in the same manner that can be compatible with the train set?

            ...

            ANSWER

            Answered 2021-Oct-08 at 00:07

            Changing the order of attributes (e.g., when using the Ranker in conjunction with an attribute evaluator) will probably not have much influence on the performance of your classifier model (since all the attributes will stay in the dataset). Removing attributes, on the other hand, will more likely have an impact (for that, use subset evaluators).

            If you want the ordering to get applied to the test set as well, then simply define your attribute selection search and evaluation schemes in the AttributeSelectedClassifier meta-classifier, instead of using the Attribute selection panel (that panel is more for exploration).

            Source https://stackoverflow.com/questions/69488957

            QUESTION

            how to split a piece text by a word in R?( break the text after a specific word)
            Asked 2021-Oct-06 at 16:10

            I need to split pdf files into their chapters. In each pdf, at the beginning of every chapter, I added the word "Hirfar" for which to look and split the text. Consider the following example:

            ...

            ANSWER

            Answered 2021-Oct-06 at 16:10

            We may use regex lookaround

            Source https://stackoverflow.com/questions/69469109

            QUESTION

            How to locate an element within bad html python selenium
            Asked 2021-Aug-26 at 07:41

            I want to scrape the Athletic Director's information from this page. but the issue is that there is a strong tag that refers to the name and email of every person on the page. I only want an XPath that specifically extracts the exact name and email of the Athletic Director. Here is the link to the website for a better understanding of the code. "https://fhsaa.com/sports/2020/1/28/member_directory.aspx"

            ...

            ANSWER

            Answered 2021-Aug-26 at 07:41

            to get the email id, use this :-

            Source https://stackoverflow.com/questions/68928190

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

            Vulnerabilities

            No vulnerabilities reported

            Install FrequentSubgraphMining

            You can download it from GitHub.
            You can use FrequentSubgraphMining 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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