Git Product home page Git Product logo

adaherf's Introduction

AdaHERF

We are going to convert Adaptative Hybrid Extreme Rotation Forest (AdaHERF) code from Matlab to Python.

References

[1] Borja Ayerdi, Manuel Grana. "Hybrid Extreme Rotation Forest",
          Neural Networks, 2014.

[2] Borja Ayerdi, Manuel Grana. "Hyperspectral Image Analysis by 
          Spectral–Spatial Processing and Anticipative Hybrid Extreme
          Rotation Forest Classification",
          IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2016.

[3] http://www.extreme-learning-machines.org 

[4] G.-B. Huang, Q.-Y. Zhu and C.-K. Siew, "Extreme Learning Machine:
          Theory and Applications", Neurocomputing, vol. 70, pp. 489-501,
          2006.
          
[5] Fernandez-Navarro, et al, "MELM-GRBF: a modified version of the  
          extreme learning machine for generalized radial basis function  
          neural networks", Neurocomputing 74 (2011), 2502-2510

adaherf's People

Contributors

alexsavio avatar borjaayerdi avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

adaherf's Issues

Memory Error

Traceback (most recent call last):
  File "C:/landslide_sklearn/algorithms/adaHERF.py", line 14, in <module>
    ada_herf.fit(X_train,y_train)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\AdaHERF.py", line 165, in fit
    ensembleComposition = self._clasProbDist(x_train, y_train)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\AdaHERF.py", line 109, in _clasProbDist
    cl.fit(x_train, y_train)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\elm.py", line 560, in fit
    self.elm_classifier_.fit(X, y)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\elm.py", line 315, in fit
    self.elm_regressor_.fit(X, y_bin)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\elm.py", line 181, in fit
    self.hidden_activations_ = self.hidden_layer.fit_transform(X)
  File "C:\Users\YD\PycharmProjects\test01\venv\lib\site-packages\sklearn\base.py", line 517, in fit_transform
    return self.fit(X, **fit_params).transform(X)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\random_hidden_layer.py", line 130, in transform
    return self._compute_hidden_activations(X)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\random_hidden_layer.py", line 71, in _compute_hidden_activations
    self._compute_input_activations(X)
  File "C:\landslide_sklearn\algorithms\AdaHERF_3rd_party\random_hidden_layer.py", line 233, in _compute_input_activations
    self.input_activations_ = safe_sparse_dot(X, w)
  File "C:\Users\YD\PycharmProjects\test01\venv\lib\site-packages\sklearn\utils\extmath.py", line 140, in safe_sparse_dot
    return np.dot(a, b)
MemoryError

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.