Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   re-investigate windowing for rule learning algorithms.  show that, contrary to previous results for decision tree learning, windowing can in fact achieve significant run-time gains in noise-free domains and explain the different behaviour of rule learning algorithms by the fact that they learn each rule independently. The main contribution of this paper is integrative windowing, a new type of algorithm that further exploits this property by integrating good rules into the final theory right after they have been discovered. Thus it avoids re-learning these rules in subsequent iterations of the windowing process. Experimental evidence in a variety of noise-free domains shows that integrative windowing can in fact achieve substantial run-time gains. Furthermore,  discuss the problem of noise in windowing and present an algorithm that is able to archieve run-time gains in a set of experiments in a simple domain with artificial noise.
['Johannes Fürnkranz']
I am writing a research paper on a idea Integrative Windowing
[{"from": "human", "value": "I am writing a research paper on a idea Integrative Windowing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   re-investigate windowing for rule learning algorithms.  show that, contrary to previous results for decision tree learning, windowing can in fact achieve significant run-time gains in noise-free domains and explain the different behaviour of rule learning algorithms by the fact that they learn each rule independently. The main contribution of this paper is integrative windowing, a new type of algorithm that further exploits this property by integrating good rules into the final theory right after they have been discovered. Thus it avoids re-learning these rules in subsequent iterations of the windowing process. Experimental evidence in a variety of noise-free domains shows that integrative windowing can in fact achieve substantial run-time gains. Furthermore,  discuss the problem of noise in windowing and present an algorithm that is able to archieve run-time gains in a set of experiments in a simple domain with artificial noise."}]