OpenNE | An Open-Source Package for Network Embedding | Machine Learning library
kandi X-RAY | OpenNE Summary
kandi X-RAY | OpenNE Summary
This repository provides a standard NE/NRL(Network Representation Learning）training and testing framework. In this framework, we unify the input and output interfaces of different NE models and provide scalable options for each model. Moreover, we implement typical NE models under this framework based on tensorflow, which enables these models to be trained with GPUs. We develop this toolkit according to the settings of DeepWalk. The implemented or modified models include DeepWalk, LINE, node2vec, GraRep, TADW, GCN, HOPE, GF, SDNE and LE. We will implement more representative NE models continuously according to our released NRL paper list. Specifically, we welcome other researchers to contribute NE models into this toolkit based on our framework. We will announce the contribution in this project.
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Top functions reviewed by kandi - BETA
- Load INDRA data
- Parse an index file
- Generate a boolean mask from a given index
- Get train layer
- Generate a batch
- Embed the model
- Train the model
- A layer of fc
- Preprocess data
- Preprocess feature matrix
- Reads an EDGE file
- Encode nodes
- Calculate training and test set
- Parse arguments
- Read a node label from a file
- Get train matrix
- Simulates a random walk
- Construct a feed dictionary
- Preprocess the features
- Train one epoch
- Build the model
- Preprocess transition probabilities
- Convert text into a networkx graph
- Convolve inputs
- Computes the Chebyshev polynomial polynomials
- Perform a deep walk
- Evaluate the input tensor
OpenNE Key Features
OpenNE Examples and Code Snippets
Lines of Code : 19License : Permissive (MIT)
Copy# Python 2
sudo apt-get install python-pip
sudo apt-get install python-tk
# Python 3
sudo apt-get install python3-pip
sudo apt-get install python3-tk
# Python 2
pip install evalne
# Python 3
pip3 install evalne
# Python 2
cd examples/
python simp 
License : No LicenseCopyjulia -e 'using Pkg; Pkg.add(url="https://github.com/KrainskiL/CGE.jl")'
julia -e 'using Pkg; Pkg.add(url="https://github.com/bkamins/ABCDGraphGenerator.jl")'
pip -r requirements.txt
git clone https://github.com/thunlp/OpenNE.git
cd src
python setu Community Discussions
Trending Discussions on OpenNE
QUESTION
users,
I have received a data from a conjoint survey experiment. What I want to do is to reshape from wide to long format. However, this seems to be slightly complicated. I am pretty sure it is possible to do with cj_tidy (package cregg) but can't solve it myself.
In the survey, the respondents were asked to compare two organizations that vary across 7 profiles (Efficiency Opennes Inclusion Leader Gain & System). In total, respondents were presented with four comparisons. So 2 organizations and 4 comparisons (4x2). They had to choose one of the presented organization and rate them separately after choosing one.
At the moment, the profile variables are structured in this way: org1_Efficiency_conj_1, org1_Opennes_conj1 ..etc. The first part "org" indicates whether it is the first or second organization. The last part "conj", indicated the order of the conjoint/comparison, where the "conj4" is the last comparison. The CHOICE variables also follow the order of conjoint – for example,"CHOICE_conj1", "CHOICE_conj2", where =1 means the respondent chose "org1". If =2, then org2 was chosen. The RATING> variable indicates a value from 0 to 10 for each organization: RATING_conj1_org1; RATING_conj1_org2 etc..
The current wide format of the data is not suitable for conjoint analysis - what I need is to create 8 observations for each respondent (4x2=8) where the variable CHOICE would indicate which of the organizations were chosen (where =1 if yes; and =0 if no). In a similar way, the variable RATING should indicate the rating given by respondents for both of the organizations (0 to 10).
This is how I would like the data to look like:
Note please that there are also covariates such as Q1 and Q2 in the picture, they are not a part of the experiment and should remain constant for each individual observation.
Below I share 50 observations from my real data.
...ANSWER
Answered 2021-Jan-20 at 23:30Your data not being in a standard form mades this a difficult problem. Here is a solution using the tidyr package.
The solutions involves 3 parts, dealing with the profiles, the rating and finally the rating choice.
The key to the profiles part was to pivot long and breaking up the profile names into component parts and then pivot wider for the column headings.
The rating and binary choice involved pivoting longer and then aligning the rows.
QUESTION
My data format is：
datas = {[1,2,4,6,7],[2,3],[5,6,8,3,5],[2],[93,23,4,5,11,3,5,2],...}
Each element in datas is a sentence ,and each number is a word.I want to get the TFIDF value for each number. How to do it with sklearn or other ways?
My code:
...ANSWER
Answered 2018-Nov-19 at 09:13You are using CountVectorizer which requires an iterable of strings. Something like:
QUESTION
I have a function that inside a function. I want the parent function to return an updated object (after the loop ends), currently, it returns undefined because the parent function returns nothing, only the child function function(items) returns data. How can I make the parent function returns updated return_data? Thanks a lot.
ANSWER
Answered 2018-Aug-23 at 10:11You can either use a callback function or write this function as a promise. Callback is a function you will pass into your function to execute after the data is done.
For the callback function: https://developer.mozilla.org/en-US/docs/Glossary/Callback_function
QUESTION
I have a table like below. There's some competencies, and each competencies has their value option to be choosed. Each competencies has total which is get from the value*weight value.
How to count the total for each competencies everytime the radio button change using jquery? The total in the right column is count by value from radio button*weight value.
Table Format:
...ANSWER
Answered 2018-Mar-26 at 08:17You see that you have id number 1, 2 and so on common for each weightvalue, radio and totalcompetency. Thus, you can set up your logic in such a way that you can detect the weight from each row and calculate total for each row uniquely when the radio button is selected by using that id number. You can understand that very well by looking at the below example.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install OpenNE
You can use OpenNE 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.
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