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Principal component analysis ( PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing . The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
Artistic director and principal conductor After a year-long selection process in the 2007/2008 season with guest conductors from four different countries, an international jury awarded the musical direction of Turkey's foremost symphony orchestra to Austrian conductor Sascha Goetzel.
Dimensionality reduction. Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can ...
Selection principle. In mathematics, a selection principle is a rule asserting the possibility of obtaining mathematically significant objects by selecting elements from given sequences of sets. The theory of selection principles studies these principles and their relations to other mathematical properties.
The principal–agent problem refers to the conflict in interests and priorities that arises when one person or entity (the "agent") takes actions on behalf of another person or entity (the "principal"). [1] The problem worsens when there is a greater discrepancy of interests and information between the principal and agent, as well as when the ...
In statistics, principal component regression ( PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model . In PCR, instead of regressing the dependent variable on the explanatory variables ...
The Fischer–Tropsch process (FT) is a collection of chemical reactions that converts a mixture of carbon monoxide and hydrogen, known as syngas, into liquid hydrocarbons. These reactions occur in the presence of metal catalysts , typically at temperatures of 150–300 °C (302–572 °F) and pressures of one to several tens of atmospheres.
Multilinear principal component analysis. Multilinear principal component analysis ( MPCA) is a multilinear extension of principal component analysis (PCA) that is used to analyze M-way arrays, also informally referred to as "data tensors". M-way arrays may be modeled by linear tensor models, such as CANDECOMP/Parafac, or by multilinear tensor ...