VIME | supervised Learning to Tabular Domain | Machine Learning library

 by   jsyoon0823 Python Version: Current License: No License

kandi X-RAY | VIME Summary

kandi X-RAY | VIME Summary

VIME is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. VIME has no bugs, it has no vulnerabilities and it has low support. However VIME build file is not available. You can download it from GitHub.

Authors: Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar. Reference: Jinsung Yoon, Yao Zhang, James Jordon, Mihaela van der Schaar, "VIME: Extending the Success of Self- and Semi-supervised Learning to Tabular Domain," Neural Information Processing Systems (NeurIPS), 2020. This directory contains implementations of VIME framework for self- and semi-supervised learning to tabular domain using MNIST dataset. To run the pipeline for training and evaluation on VIME framwork, simply run python3 -m main_vime.py or see jupyter-notebook tutorial of VIME in tutorial_vime.ipynb. Note that any model architecture can be used as the encoder and predictor models such as CNNs.
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              VIME has a low active ecosystem.
              It has 97 star(s) with 22 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 9 have been closed. On average issues are closed in 3 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of VIME is current.

            kandi-Quality Quality

              VIME has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              VIME 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

              VIME releases are not available. You will need to build from source code and install.
              VIME has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed VIME and discovered the below as its top functions. This is intended to give you an instant insight into VIME implemented functionality, and help decide if they suit your requirements.
            • Train VIME - Self - Self Estimation
            • VIME model
            • Simple MLP algorithm
            • VIME estimator
            • Load MNIST dataset
            • Train the supervised model
            • Generate pretext matrix
            • Logistic regression
            • Perform classification on training dataset
            • Convert a vector
            • Convert a matrix to a vector
            • Compute the accuracy metric
            • Generate a binary mask
            Get all kandi verified functions for this library.

            VIME Key Features

            No Key Features are available at this moment for VIME.

            VIME Examples and Code Snippets

            No Code Snippets are available at this moment for VIME.

            Community Discussions

            QUESTION

            how can i fix this NullExceptionPointer error?
            Asked 2020-Jul-28 at 20:54

            Hey this is ready made code from a Maple Story game That I run a function for me it works for others does not They do not get a timer. seems chr.getFitness() returning null I'm not strong in java I would love if someone would help. Error 1 img

            Also they cant pass last stage in game Error 2 img

            MapleFitness Script

            ...

            ANSWER

            Answered 2020-Jul-28 at 20:54

            Check if the MapleFitness is null and if it is, then create the object before returning like this

            Source https://stackoverflow.com/questions/63020226

            QUESTION

            How to filter a data.frame by matching a character string?
            Asked 2020-Jul-08 at 17:11

            I have those structures:

            ...

            ANSWER

            Answered 2020-Jul-07 at 22:59

            Using the solution from this answer.

            Source https://stackoverflow.com/questions/62784381

            QUESTION

            SQL Server using inner join on 2 databases with different SQL authentication credentials
            Asked 2018-Apr-16 at 11:58

            This probably can't be done, but thought I'd ask anyway.

            On my SQL Server I have 2 databases, each has different SQL Authentication credentials - different usernames and passwords on each one as each are used by different programs.

            What I want to do is an inner join query which links 2 tables, one from each database.

            If it was Just Windows authentication, I could use something like:

            ...

            ANSWER

            Answered 2018-Apr-16 at 11:58

            I think the best way to show this is with a script. This is pretty much self explanatory, however, if you have any question, please comment:

            Source https://stackoverflow.com/questions/49854804

            QUESTION

            Generate Usernames in Python
            Asked 2018-Apr-08 at 05:21

            I have a text file studentlist.txt which reads as follows:

            studentlist.txt

            ...

            ANSWER

            Answered 2018-Apr-08 at 04:58
            usernames = []
            count = 1 #put countoutside
            for line in open('studentlist.txt'):
            
              name = line.lower().split()
              surname = name[-1]
              username = ''.join(name[0:-1])
              username_w_surname = username + surname[0]
              username_w_surname_integer = username_w_surname + str(count)
            
              if username not in usernames:
                usernames.append(username)
              elif username_w_surname not in usernames:
                usernames.append(username_w_surname)
              else:
                count = count + 1
                usernames.append(username_w_surname_integer)
            for entry in usernames:
              print (entry)
            
            
            sam
            samf
            samg
            samc
            samv
            samv1
            samv2
            

            Source https://stackoverflow.com/questions/49714426

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

            Vulnerabilities

            No vulnerabilities reported

            Install VIME

            You can download it from GitHub.
            You can use VIME 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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