Self-Organizing Neural Networks

Pattern recognition is a part of machine learning that focuses on the recognition of patterns and regularities in data by using supervised learning algorithms that create classifiers based on training data from different object classes. Optical character recognition (OCR) faces detection, face recognition, object detection, and object classification uses supervised pattern recognition. And the unsupervised learning works by finding hidden structures in clustering techniques.

Feature selection or variable selection, is the process of selecting a subset of relevant features for use in model construction. They are also used to simplify the models to make them easier to interpret, shorter training times and enhanced generalisation by reducing over fitting (reduction of variables). The data contains many features that are either redundant or irrelevant, and can be removed without incurring much loss of information.

  • Face Recognition Using Artificial Neural Network
  • Non Parametric Neural Network
  • Self-Organizing Neural Network For Non-Parametric Regression Analysis
  • Recurrent Neural Networks And Reservoir Computing

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