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Dreamlone commented Jul 1, 2021

A possible improvement of the time series smoothing operation is proposed. Below is example of applying smoothed operation

Currently, the implementation of smoothing allows modifying only the "features" time series (features field in InputData/OutputData). But it does not change the

Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

  • Updated Jul 21, 2021
  • Python
Sceki commented Jun 9, 2019

Some problems/algorithms seem to have an inconsistent python exposition in terms of types.

For instance, in ../src/problems/dtlz.cpp we have:

dtlz::dtlz(unsigned prob_id, vector_double::size_type dim, vector_double::size_type fdim, unsigned alpha)

But in the ../pygmo/expose_problems_0.cpp it is exposed as:

dtlz_p.def(bp::init<unsigned, unsigned, unsigned, unsigned>



zoofs is a Python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

  • Updated Sep 19, 2021
  • Python

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