Ho–Kashyap rule: Difference between revisions

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{{Short description|Iterative method for finding a linear decision boundary}}

{{Use dmy dates|date=May 2024}}

The '''Ho–Kashyap algorithm''' is an iterative method in [[machine learning]] for finding a [[linear classifier|linear decision boundary]] that separates two [[Linear separability|linearly separable]] classes. It was developed by [[Yu-Chi Ho]] and [[Rangasami L. Kashyap]] in 1965,<ref>{{Cite journal |last=Ho |first=Y-C. |last2=Kashyap |first2=R. L. |date=October 1965-10 |title=An Algorithm for Linear Inequalities and its Applications |url=http://ieeexplore.ieee.org/document/4038553/ |journal=IEEE Transactions on Electronic Computers |volume=EC-14 |issue=5 |pages=683–688 |doi=10.1109/PGEC.1965.264207 |issn=0367-7508|url-access=subscription }}</ref><ref>{{Cite journal |last=Ho |first=Yu-Chi |last2=Kashyap |first2=R. L. |date=February 1966-02 |title=A Class of Iterative Procedures for Linear Inequalities |url=http://epubs.siam.org/doi/10.1137/0304010 |journal=SIAM Journal on Control |language=en |volume=4 |issue=1 |pages=112–115 |doi=10.1137/0304010 |issn=0036-1402|url-access=subscription }}</ref> and usually presented as a problem in [[linear programming]].

== Setup ==