Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A fast Newton method, that suppresses input space features, is proposed for a linear programming formulation of support vector machine classifiers. The proposed stand-alone method can handle classification problems in very high dimensional spaces, such as 28,032 dimensions, and generates a classifier that depends on very few input features, such as 7 out of the original 28,032. The method can also handle problems with a large number of data points and requires no specialized linear programming packages but merely a linear equation solver. For nonlinear kernel classifiers, the method utilizes a minimal number of kernel functions in the classifier that it generates.
['Glenn Fung', 'Olvi L. Mangasarian']
I am writing a research paper on a idea A Feature Selection Newton Method for Support Vector Machine Classification
[{"from": "human", "value": "I am writing a research paper on a idea A Feature Selection Newton Method for Support Vector Machine Classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A fast Newton method, that suppresses input space features, is proposed for a linear programming formulation of support vector machine classifiers. The proposed stand-alone method can handle classification problems in very high dimensional spaces, such as 28,032 dimensions, and generates a classifier that depends on very few input features, such as 7 out of the original 28,032. The method can also handle problems with a large number of data points and requires no specialized linear programming packages but merely a linear equation solver. For nonlinear kernel classifiers, the method utilizes a minimal number of kernel functions in the classifier that it generates."}]