MFE-CRF | Aspect Term Extraction Based on MFE-CRF | Data Labeling library

 by   xymcsu Python Version: Current License: No License

kandi X-RAY | MFE-CRF Summary

kandi X-RAY | MFE-CRF Summary

MFE-CRF is a Python library typically used in Artificial Intelligence, Data Labeling applications. MFE-CRF has no bugs, it has no vulnerabilities and it has low support. However MFE-CRF build file is not available. You can download it from GitHub.

Aspect Term Extraction Based on MFE-CRF
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            kandi-support Support

              MFE-CRF has a low active ecosystem.
              It has 5 star(s) with 0 fork(s). There are no watchers for this library.
              OutlinedDot
              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 MFE-CRF is current.

            kandi-Quality Quality

              MFE-CRF has no bugs reported.

            kandi-Security Security

              MFE-CRF has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

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

            kandi-Reuse Reuse

              MFE-CRF releases are not available. You will need to build from source code and install.
              MFE-CRF has no build file. You will be need to create the build yourself to build the component from source.

            Top functions reviewed by kandi - BETA

            kandi has reviewed MFE-CRF and discovered the below as its top functions. This is intended to give you an instant insight into MFE-CRF implemented functionality, and help decide if they suit your requirements.
            • Train word2Vec
            • Lemmatize text
            • Split the corpus
            • Create list of lemm_tags
            • Calculate baseline for resturant
            • Takes a list of test instances
            • Yield offsets from the given text
            • Return a list of offsets
            • Takes a list of test_instances
            • Return the majority of text
            • Compute the k - nearest neighbors of the given text
            • Returns the dice similarity between two tokens
            • Evaluate train and test features
            • Load dependencies
            • This method is used to process deps
            • Creates the dependencies for the given dep_path
            • Function to create a new cluster
            • Load a word2vec
            • Work out k - means clustering
            • Creates all dependencies
            • A helper method to create the dependency information
            • Creates the NER tag
            • Takes a file and creates a BioClassifier
            Get all kandi verified functions for this library.

            MFE-CRF Key Features

            No Key Features are available at this moment for MFE-CRF.

            MFE-CRF Examples and Code Snippets

            No Code Snippets are available at this moment for MFE-CRF.

            Community Discussions

            QUESTION

            How can I do this split process in Python?
            Asked 2021-Dec-30 at 14:06

            I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

            What I've done so far is make this representation with the same enumerator class.

            A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

            ...

            ANSWER

            Answered 2021-Dec-30 at 13:57

            Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

            Source https://stackoverflow.com/questions/70532286

            QUESTION

            Replacing a character with a space and dividing the string into two words in R
            Asked 2020-Nov-18 at 07:32

            I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

            In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

            i have this:

            ...

            ANSWER

            Answered 2020-Nov-16 at 07:24

            QUESTION

            Azure ML FileDataset registers, but cannot be accessed for Data Labeling project
            Asked 2020-Oct-28 at 20:31

            Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

            Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

            Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

            ...

            ANSWER

            Answered 2020-Oct-27 at 22:39

            Is the data behind virtual network by any chance?

            Source https://stackoverflow.com/questions/64546521

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

            Vulnerabilities

            No vulnerabilities reported

            Install MFE-CRF

            You can download it from GitHub.
            You can use MFE-CRF 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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            https://github.com/xymcsu/MFE-CRF.git

          • CLI

            gh repo clone xymcsu/MFE-CRF

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            git@github.com:xymcsu/MFE-CRF.git

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