Law of Connectivity in Machine Learning
Abstract
We present in this paper our law that there is always a connection present between two entities, with a selfconnection being present at least in each node. An entity is an object, physical or imaginary, that is connected by a path (or connection) and which is important for achieving the desired result of the scenario. In machine learning, we state that for any scenario, a subject entity is always, directly or indirectly, connected and affected by single or multiple independent / dependent entities, and their impact on the subject entity is dependent on various factors falling into the categories such as the existenc
Cite
@article{arxiv.1107.0194,
title = {Law of Connectivity in Machine Learning},
author = {Jitesh Dundas},
journal= {arXiv preprint arXiv:1107.0194},
year = {2011}
}
Comments
Keywords- Machine Learning; unknown entities; independence; interaction; coverage, silent connections; ISSN 1473-804x online, 1473-8031 print