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:
“According to the historian, they escaped as by a miracle all roving bands of Indians, and reached their homes in safety, with their trophies, for which the General Court paid them fifty pounds. The family of Hannah Dustan all assembled alive once more, except the infant whose brains were dashed out against the apple tree, and there have been many who in later time have lived to say that they have eaten of the fruit of that apple tree.”
—Henry David Thoreau (1817–1862)
“[The Republican Party] consists of those who, believing in the doctrine that mankind are capable of governing themselves and hating hereditary power as an insult to the reason and an outrage to the rights of men, are naturally offended at every public measure that does not appeal to the understanding and to the general interest of the community.”
—James Madison (1751–1836)
“As to the rout that is made about people who are ruined by extravagance, it is no matter to the nation that some individuals suffer. When so much general productive exertion is the consequence of luxury, the nation does not care though there are debtors in gaol; nay, they would not care though their creditors were there too.”
—Samuel Johnson (1709–1784)