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  2. 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 ...

  3. 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.

  4. 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.

  5. Robust principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Robust_principal_component...

    The 2014 guaranteed algorithm for the robust PCA problem (with the input matrix being = +) is an alternating minimization type algorithm. [12] The computational complexity is (⁡) where the input is the superposition of a low-rank (of rank ) and a sparse matrix of dimension and is the desired accuracy of the recovered solution, i.e., ‖ ^ ‖ where is the true low-rank component and ^ is the ...

  6. Percentage-of-completion method - Wikipedia

    en.wikipedia.org/wiki/Percentage-of-Completion...

    The accounting for long term contracts using the percentage of completion method is an exception to the basic realization principle. This method is used wherein the revenues are determined based on the costs incurred so far. The percentage of completion method is used when: Collections are assured; The accounting system can: Estimate profitability

  7. Contribution margin - Wikipedia

    en.wikipedia.org/wiki/Contribution_margin

    In Cost-Volume-Profit Analysis, where it simplifies calculation of net income and, especially, break-even analysis.. Given the contribution margin, a manager can easily compute breakeven and target income sales, and make better decisions about whether to add or subtract a product line, about how to price a product or service, and about how to structure sales commissions or bonuses.

  8. 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 ...

  9. Independent component analysis - Wikipedia

    en.wikipedia.org/wiki/Independent_component_analysis

    In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. [1]