RandPro v0.2.0

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Random Projection with Classification

Performs random projection using Johnson-Lindenstrauss (JL) Lemma (see William B.Johnson and Joram Lindenstrauss (1984) <doi:10.1090/conm/026/737400>). Random Projection is a dimension reduction technique, where the data in the high dimensional space is projected into the low dimensional space using JL transform. The original high dimensional data matrix is multiplied with the low dimensional projection matrix which results in reduced matrix. The projection matrix can be generated using the projection function that is independent to the original data. Then finally apply the classification task on the projected data.

Functions in RandPro

Name Description
classify Classification Function
dimension Function to determine the required number of dimension for generating the projection matrix
form_matrix Forms the Projection Matrix
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Details

Type Package
License GPL (>= 2)
Encoding UTF-8
LazyData TRUE
RoxygenNote 6.0.1
Repository CRAN
NeedsCompilation no
Packaged 2018-01-09 12:08:35 UTC; NIT
Date/Publication 2018-01-10 06:46:06 UTC
depends caret
imports e1071 , stats
Contributors Aghila G, Siddharth R

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