Linear Algebra - Projection

Data Mining - (Feature|Attribute) Extraction Function

Data Mining - (Feature|Attribute) Extraction Function About Feature extraction is the second class of methods for dimension reduction. dimension reduction It creates new attributes (features) u "...

Data Mining - Principal Component (Analysis|Regression) (PCA|PCR)

Principal Component Analysis (PCA) is a feature extraction method that use orthogonal linear projections to capture the underlying variance of the data. By far, the most famous dimension reduction ap "...

Linear Algebra - Closest point in higher dimension than a plane

Solving closest point in the span of many vectors Goal: An algorithm that, given a vector b and vectors v1, . . . , vn, finds the vector in Span {v1, . . . , vn} that is closest to bb is in Span {v1, "...

Linear Algebra - Orthogonalization - Building an orthogonal set of generators

Original stated goal: Find the projection of b orthogonal to the space V spanned by arbitrary vectors Articles Related Computation Input: A list of vectors over the reals output: A list of mutually "...

Spatial - Projection

See Projections: summarizing mutli-dimensional data in two or three dimensions. Articles Related Example Data Projections Scale projection function Data domain Pixel Range DateTime (Years, Month, Dat "...