Feature Extraction - General

General

Feature extraction involves simplifying the amount of resources required to describe a large set of data accurately. When performing analysis of complex data one of the major problems stems from the number of variables involved. Analysis with a large number of variables generally requires a large amount of memory and computation power or a classification algorithm which overfits the training sample and generalizes poorly to new samples. Feature extraction is a general term for methods of constructing combinations of the variables to get around these problems while still describing the data with sufficient accuracy.

Best results are achieved when an expert constructs a set of application-dependent features. Nevertheless, if no such expert knowledge is available general dimensionality reduction techniques may help. These include:

  • Principal component analysis
  • Semidefinite embedding
  • Multifactor dimensionality reduction
  • Multilinear subspace learning
  • Nonlinear dimensionality reduction
  • Isomap
  • Kernel PCA
  • Multilinear PCA
  • Latent semantic analysis
  • Partial least squares
  • Independent component analysis
  • Autoencoder

Read more about this topic:  Feature Extraction

Famous quotes containing the word general:

    “The esteem of good men is the reward of our worth, but the reputation of the world in general is the gift of our fate.”
    —François, Duc De La Rochefoucauld (1613–1680)

    “The conclusion suggested by these arguments might be called the paradox of theorizing. It asserts that if the terms and the general principles of a scientific theory serve their purpose, i. e., if they establish the definite connections among observable phenomena, then they can be dispensed with since any chain of laws and interpretive statements establishing such a connection should then be replaceable by a law which directly links observational antecedents to observational consequents.”
    —C.G. (Carl Gustav)

    “The general tendency of things throughout the world is to render mediocrity the ascendant power among mankind.”
    —John Stuart Mill (1806–1873)