Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The imbalanced nature of some real-world data is one of the current challenges for machine learning, giving rise to dierent approaches to handling it. Hover, preprocessing methods operate in the original in- put space, presenting distortions when combined with the kernel classiers, which make use of the feature space.  explores the notion of empirical feature space (a Euclidean space which is isomorphic to the fea- ture space) to develop a kernel-based synthetic over-sampling technique, which maintains the main properties of the kernel mapping. The proposal achieves better results than the same oversampling method applied to the original input space.
['María Pérez-Ortiz', 'Pedro Antonio Gutiérrez', 'César Hervás-Martínez']
I am writing a research paper on a idea Synthetic over-sampling in the empirical feature space
[{"from": "human", "value": "I am writing a research paper on a idea Synthetic over-sampling in the empirical feature space"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The imbalanced nature of some real-world data is one of the current challenges for machine learning, giving rise to dierent approaches to handling it. Hover, preprocessing methods operate in the original in- put space, presenting distortions when combined with the kernel classiers, which make use of the feature space.  explores the notion of empirical feature space (a Euclidean space which is isomorphic to the fea- ture space) to develop a kernel-based synthetic over-sampling technique, which maintains the main properties of the kernel mapping. The proposal achieves better results than the same oversampling method applied to the original input space."}]