Essays about: "autoencoder dimensionality reduction attribute elimination"

Found 1 essay containing the words autoencoder dimensionality reduction attribute elimination.

  1. 1. Redundant and Irrelevant Attribute Elimination using Autoencoders

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Tim Granskog; [2017]
    Keywords : autoencoder dimensionality reduction attribute elimination;

    Abstract : Real-world data can often be high-dimensional and contain redundant or irrelevant attributes. High-dimensional data are problematic for machine learning as the high dimensionality causes learning to take more time and, unless the dataset is sufficiently large to provide an ample number of samples for each class, the accuracy will suffer. READ MORE