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  2. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    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.

  3. L1-norm principal component analysis - Wikipedia

    en.wikipedia.org/wiki/L1-norm_principal...

    In ()-(), L1-norm ‖ ‖ returns the sum of the absolute entries of its argument and L2-norm ‖ ‖ returns the sum of the squared entries of its argument.If one substitutes ‖ ‖ in by the Frobenius/L2-norm ‖ ‖, then the problem becomes standard PCA and it is solved by the matrix that contains the dominant singular vectors of (i.e., the singular vectors that correspond to the highest ...

  4. Chart of accounts - Wikipedia

    en.wikipedia.org/wiki/Chart_of_accounts

    The structure and headings of accounts should assist in consistent posting of transactions. Each nominal ledger account is unique, which allows its ledger to be located. The accounts are typically arranged in the order of the customary appearance of accounts in the financial statements: balance sheet accounts followed by profit and loss accounts.

  5. Kernel principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Kernel_principal_component...

    Output after kernel PCA, with a Gaussian kernel. Note in particular that the first principal component is enough to distinguish the three different groups, which is impossible using only linear PCA, because linear PCA operates only in the given (in this case two-dimensional) space, in which these concentric point clouds are not linearly separable.

  6. List of business and finance abbreviations - Wikipedia

    en.wikipedia.org/wiki/List_of_business_and...

    CAO – Chief administrative officer or chief accounting officer; CAPEX – Capital expenditure; CAPM – Capital asset pricing model [1] CBOE – Chicago Board Options Exchange; CBOT – Chicago Board of Trade; CDO – Collateralized debt obligation or chief data officer; CDM – Change and data management; CDS – Credit default swap; CEO ...

  7. Principal component regression - Wikipedia

    en.wikipedia.org/wiki/Principal_component_regression

    In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). PCR is a form of reduced rank regression. [1] More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model.

  8. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    In the statistical analysis it is necessary to take into account this structure. This is the aim of multiple factor analysis which balances the different issues (i.e. the different groups of variables) within a global analysis and provides, beyond the classical results of factorial analysis (mainly graphics of individuals and of categories ...

  9. Sparse PCA - Wikipedia

    en.wikipedia.org/wiki/Sparse_PCA

    Sparse principal component analysis (SPCA or sparse PCA) is a technique used in statistical analysis and, in particular, in the analysis of multivariate data sets. It extends the classic method of principal component analysis (PCA) for the reduction of dimensionality of data by introducing sparsity structures to the input variables.