Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Probability density function (PDF) estimation is a very critical task in many applications of data analysis. For example in the Bayesian framework decisions are taken according to Bayes' rule, which directly involves the evaluation of the PDF. Many methods are available to this aim, but there is no consensus in the literature about which to use, nor about the pros and cons of each of them. ,  present a thorough and extensive experimental comparison beten two of the most popular methods: Parzen window and finite Gaussian mixture. Extended experimental results and application development guidelines are reported.
['Cédric Archambeau', 'Maurizio Valle', 'A. Assenza', 'Michel Verleysen']
I am writing a research paper on a idea Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures
[{"from": "human", "value": "I am writing a research paper on a idea Assessment of probability density estimation methods: Parzen window and finite Gaussian mixtures"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Probability density function (PDF) estimation is a very critical task in many applications of data analysis. For example in the Bayesian framework decisions are taken according to Bayes' rule, which directly involves the evaluation of the PDF. Many methods are available to this aim, but there is no consensus in the literature about which to use, nor about the pros and cons of each of them. ,  present a thorough and extensive experimental comparison beten two of the most popular methods: Parzen window and finite Gaussian mixture. Extended experimental results and application development guidelines are reported."}]