Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the decision process.   aim to overcome this issue of comprehensibility by learning a single decision tree that approximates an ensemble of decision trees. The new model is obtained by exploiting the class distributions predicted by the ensemble. These are employed to compute heuristics for deciding which tests are to be used in the new tree. As such  acquire a model that is able to give insight in the decision process, while being more accurate than the single model directly learned on the data. The proposed method is experimentally evaluated on a large number of UCI data sets, and compared to an existing approach that makes use of artificially generated data.
['Anneleen Van Assche', 'Hendrik Blockeel']
I am writing a research paper on a idea Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble
[{"from": "human", "value": "I am writing a research paper on a idea Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the decision process.   aim to overcome this issue of comprehensibility by learning a single decision tree that approximates an ensemble of decision trees. The new model is obtained by exploiting the class distributions predicted by the ensemble. These are employed to compute heuristics for deciding which tests are to be used in the new tree. As such  acquire a model that is able to give insight in the decision process, while being more accurate than the single model directly learned on the data. The proposed method is experimentally evaluated on a large number of UCI data sets, and compared to an existing approach that makes use of artificially generated data."}]