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I am working on a Java project, and I have to compute a multiple linear regression, but I want the gotten parameters to be non-negative. Is there an existing commercial-friendly-licensed library to do such a thing? I've been looking for Non-Negative Least Squares libs, without success.

Thank you for your help.

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2 Answers 2

up vote 1 down vote

Have your tried Weka? It's Java and under GNU General Public License. It's mainly a GUI-Tool for experiments, but you can use it as a library too. It should have implementations of linear regressions.

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Thank you for answer but Weka does not seem to have the features I need. I have not found non-negative linear regression, nor multiple linear regression. Maybe I've missed something? –  Cedric Buron Nov 26 '13 at 11:32
    
not sure what "logistic" means, but what about weka.sourceforge.net/doc.packages/supervisedAttributeScaling/…? –  Thomas Uhrig Nov 26 '13 at 12:43
    
Thank you much. Logistic regression is different from linear regression, quite far actually. It is actually a binary predictor. –  Cedric Buron Nov 26 '13 at 13:02
up vote 0 down vote accepted

Well, I could not find any pure java library so I built it myself from the article of [1], wich can be found in [2] and [3]. I give the algorithm:

P, R are the active and the passive sets. t() is transpose

The problem is to solve Ax = b under the condition x>0

P=null
R = {1,2,...,m}
x = 0
w = t(A)*(b-A*x)
while R<>null and max{wi|i in R}>0 do:
    j = argmax{wi|i in R}
    P = P U {j}
    R = R\{j}
    s[P] = invert[t(A[P])A[P]]t(A[P])b
    while sp<=0 do:
        a = -min{xi/(di-xi)|i in P and di<0}
        x = x + a*s -x
        update(P)
        update(R)
        sP = invert[t(A[P])A[P]]t(A[P])b
        sR = 0
    x = s
    w = t(A)*(b-A*x)
return x

For the other definitions, I strongly advise to read the papers [2] and [3], which are online (see below for the links ;) )

[1] Lawson, C. L., & Hanson, R. J. (1974). Solving least squares problems (Vol. 161). Englewood Cliffs, NJ: Prentice-hall. [2] Rasmus Bro et Sijmen De Jong : A fast non-negativity-constrained least squares algorithm. Journal of chemometrics, 11(5) :393–401, 1997. http://www.researchgate.net/publication/230554373_A_fast_non-negativity-constrained_least_squares_algorithm/file/79e41501a40da0224e.pdf [3] Donghui Chen et Robert J Plemmons : Nonnegativity constraints in numerical analysis. In Symposium on the Birth of Numerical Analysis, pages 109–140, 2009. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.157.9203&rep=rep1&type=pdf

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