IBSEAD - distributed autonomous entity systems based Interaction
IBSEAD: - A self-evolving self-obsessed learning algorithm for machine learning IBSEAD stands for distributed autonomous entity systems based Interaction - a learning algorithm that tends to self-evolve.
IBSEAD: - A self-evolving self-obsessed learning algorithm for machine learning IBSEAD stands for distributed autonomous entity systems based Interaction - a learning algorithm that tends to self-evolve. This algorithm was developed by Mr. Jitesh Dundas and Dr. David Chik in Oct 2010 and published in Nov 2010 in the journal IJCSET . One of the advantages of IBSEAD is that it tends to overcome some of the issues in Neural Networks and other algorithms in machine learning. One of the important features of IBSEAD is the ability to detect unknown entities. Most of the existing algorithms fail to consider these entities. Most of the algorithms limit themselves to known and hidden entities. These are the entities for which there is no information available. The authors have kept the algorithm confidential partially citing professional reasons. However, the following are the steps that are available in the original paper in the journal The international journal of Computer Science & Emerging Technologies (IJCSET). 'The algorithm has the following steps': IBSEAD scores above the Hidden Markov models (HMM) due to the presence of unknown entities.