Is there a Python package available that has RReliefF feature selection for regression targets implemented?
Theoretical and Empirical Analysis of ReliefF and RReliefF
https://link.springer.com/article/10.1023/A:1025667309714
I found an implementation from sklearn-relief package:
https://gitlab.com/qafir/sklearn-relief
Related
I have a need to calculate the CDF of a truncated normal distribution in an AnyLogic model. I haven't found any java packages that would work (but would take recommendations). I did find a package in R called truncnorm that will work for me. However, I'm struggling to figure out the best way to call the truncnorm R package. I'm experimenting with JRI in the rJava package. My plan is to add JRI as a .jar file to the Dependencies section of my AnyLogic model but I'm struggling to get it working so far.
Any other suggestions for how to do this before I keep beating my head against the wall with JRI?
If you can do the same thing in Python, you can easily call it from AnyLogic by using AnyLogic Pypeline.
I need to implement unsupervised neural network using Octave. For that, I need to use "selforgmap" function. How do I find that function in octave or what are the packages include this function?
When I use "selforgmap", I got an error like this.
selforgmap
error: 'selforgmap' undefined near line 1 column 1
help selforgmap
error: help: 'selforgmap' not found
As of now there does not appear to be any implementation of selforgmap in octave or any of it's packages. The current neural net package, nnet, can be found at Octave Forge and the Function Reference link will show you everything currently included.
The link Andy commented with above to a current reworking if the nnet package also does not currently include selforgmap, but this could obviously change. The included function files can be seen inside the inst folder.
if MATLAB's selforgmap is not an option for you, you will either need to code your own implementation or switch bto another programming language. A quick search does reveal a Python implementation of selforgmap that may serve your purpose.
I have found the following information in paper by Andrew Reynolds and co -authors "Model Finding for Recursive Functions in SMT"
"If CVC4’s finite model finding mode for recursive functions is enabled (using the command-line option
--fmf-fun)"
But I have install current version of CVC4, --fmf-fun is not available in CVC4?Can you please guide me in this.
The option --fmf-fun is not available in the latest stable release (1.4), however, it is available in the latest development release.
You can download the latest development version of CVC4 at http://cvc4.cs.nyu.edu/downloads/ (on the right of the page).
Program: Matlab R2014a.
Issues:
I tries to translate matlab code to Cortex-M3 C code by Matlab code.
The following error message shown:
"??? The library 'ImfilterBuildable' is not supported by the current target, language or compiler."
I can not find related information by key word "ImfilterBuildable".
And it is workable when choose the platform as "Host computer".
Do any one can support this issue?
Thanks in advance.
Albert Ke
In R2014a, imfilter used platform specific libraries in generated code. So only the platforms which is usually the host computer was supported for code generation. In the latest release imfilter generates code for other targets and uses platform specific libraries only for host computer targets.
In short, imfilter is not supported for Cortex-M3 code generation in R2014a.
You can see R2014a documentation for imfilter at http://www.mathworks.com/help/releases/R2014a/images/ref/imfilter.html
Latest documentation is at
http://www.mathworks.com/help/images/ref/imfilter.html
Check out the code generation section in both.
Due to http://hart.sourceforge.net/, code generation should work for rt_preempt kernels, when using scilab 5.3.2 and hart toolsbox.
I installed both on ubuntu 12.04 LTS sucessfully, but I'm kind of lost with the code generation. I use one of the hart toolbox examples (realtime_demo), and try to compile and generate code.
First off all: Are these samples supposed to work with rt_preempt or only with RTAI? what code generation commands do I have to use for rt_preempt kernels?
If anybody managed code generation for rt_preempt kernels, I would aapreciate every hint I can get!
Code generation for rt_preempt is automatically enabled, if the hart-toolbox did not detect RTAI during installation. Thus, if you don't have RTAI, by compiling your schematic you should get code that runs using rt_preemption (if this is also not available, then your code will run as a normal Linux process). However at the moment there is no way to get data in or out of the real-time process, as the RTAI scopes, meters can not be used. To overcome this communication issue and also other limitations of Xcos concerning the implementation of real-time systems, you could also have a look at OpenRTDynamics as an alternative.