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matlab2tikz / matlab2tikz

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Accept string inputs instead of char arrays

egeerardyn
egeerardyn commented Apr 16, 2018

Since MATLAB R2016b, TMW introduced "strings" as a new data type to represent strings (in contrast to the old character arrays). See e.g. https://blogs.mathworks.com/loren/2018/04/13/accept-string-inputs-in-your-code/ for more information.

We, also, should make sure that at least we can handle such string inputs. Internally, we will not be able to get rid of character arrays (for forward/backwa

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feature request matlab +0.0.1 good first issue

casadi / casadi

Star 993

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.

python c-plus-plus library modular optimization matlab mathematics nonlinear octave numerical-calculations scientific-computing derivatives code-generation parameter-estimation academic-project optimal-control symbolic-manipulation algorithmic-differentation nonlinear-programming
  • Updated Jun 9, 2022
  • C++

TheAlgorithms / MATLAB-Octave

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Add more algorithms!

13
cozek
cozek commented Oct 10, 2019

EDIT 6/10/20: If you are making a PR for hacktoberfest, please say so in your PR description so that I can add
the hacktoberfest-accepted label.

This repo needs more algorithms. If you see any missing algorithms, kindly contribute.
Hackotberfest participants are welcome!
I will list some of the algorithms that are up for grabs. However, please check if the algorithm
is already in ou

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help wanted good first issue hacktoberfest

liquidSVM / liquidSVM

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Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.

python c-plus-plus machine-learning r apache-spark matlab svm ml regression octave classification rstats r-package quantile-regression expectile-regression
  • Updated Feb 20, 2020
  • C++

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