rewrite from Matlab to R a computational model of word meaning
$300-1500 USD
Dibatalkan
Disiarkan hampir 17 tahun yang lalu
$300-1500 USD
Dibayar semasa penghantaran
EDIT: some bidders requested line counts.
They are as follows:
3143 lines in .m files
4043 lines in asv files
3276 lines in cpp/c code. No need to port that, just plug it into the resulting R code.
The code looks well written and well commented.
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THis project requires someone familiar with R ([login to view URL]), the statistical programming language.
I'd need you to recode a model (written by someone else) from Matlab to R.
I have some code for alternative models in R. R is very similar to Matlab so recoding should not be very difficult.
The application I want to recode is:
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This model can find the similarity between word meanings. For example, it could tell you that similarity(dog, cat) is higher than similarity(dog, superman). Of course, it does more interesting stuff :)
The model deals with sparse matrices. There is an excellent sparse matrix package in R called Matrix here:
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and many other useful packages in general:
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The matlab package comes with code examples, and datasets. I'd need you to test your R implementation against those examples, and make sure it produces similar results.
It has some .cpp parts, compiled as .dlls. The full source code is available in any case. You could simply reuse that .cpp code.
I don't need you to deal with documentation, as long as the R code is well-commented, I can figure out how to use it with the matlab docs.
The code should be tested to work under windows.
Dear Sir , We have all necessary skills in this area. We use most advanced
technologies and offer qualified technical assistance. Quality and satisfaction
are guaranteed. If there are any questions, we have support service.
The best regards, Gorasoft
Sir: I am an automotive engineer with over 9 years using Matlab and developing Matlab-based applications (c/mex/ etc.). Not so much experience on the R side but the project seems doable within 30-40 days timeframe. Let me know.