Could entropy be used effectively in collaboration with machine learning techniques to produce most accurate results in detection among big data?

More Xenofon Vassilakopoulos's questions See All

Can anyone help with FCM clustering?

Does anybody know if scikit-fuzzy is available for FCM clustering? Any suggestions of what programming language I should use? Thanks

08 September 2014 7,031 4 View

How to compare two groups with only two measurements?

Hiiiii everyone! I have an enquiry on statistical analysis. I was looking for many forum and it's still cannot solve my problem. I want to compare means of two groups of data but only with two...

03 March 2021 8,796 3 View

Why should we choose deep learning to machine learning? Why is CNN better for image classification? Can I get Typical Answer?

What Characteristics makes CNN work better?

03 March 2021 1,458 4 View

What are some of the research gaps in machine learning and artificial intelligence in africa?

i would to know some of the research gaps in the artificial intelligence field in most african countries.

03 March 2021 6,145 3 View

Anyone plz suggest relevant topic for research in image processing+Deep learning.?

I have selected brain tumor images ...but now found that already lots of research done n this topic.

03 March 2021 5,774 3 View

What's the best way to measure growth rates in House sparrow chicks from day 2 to day 10?

What's the best way to measure growth rates in House sparrow chicks from day 2 to day 10? Since, the growth curve from day 2 to 10 won't be like the "Logistic curve" it might not follow logistic...

03 March 2021 1,401 3 View

How to increase a model accuracy ?

dear community, my model is based feature extraction from non stationary signals using discrete Wavelet Transform and then using statistical features then machine learning classifiers in order to...

03 March 2021 6,994 5 View

1. What is the impact of having different scales in a survey? and how can we solve this problem before and after data collection (Literature)?

1. What is the impact of having different scales in a survey? and how can we solve this problem before and after data collection (Literature-based reflection)? Thank you for your time and for...

03 March 2021 2,870 3 View

What degree of missing data in a particular case/participant results in Expectation-Maximisation no longer working?

I'm dealing with a mediation model and am using the PROCESS module in SPSS. Due to SPSS and PROCESS being limited in the imputation methods - being unable to handle multiple imputation - the other...

02 March 2021 4,362 1 View

Can you share me how teacher education is managed in your respective national educational system?

I feel that the practice in teacher education in my country is below the expected performance level due to very poor management system. Hope I will learn something from your experiences.

02 March 2021 1,516 4 View

Can NFL theorem be valid in infinite search space in ML?

NFL theorem is valid for algorithms training in fixed training set. However, the general characteristic of algorithms in expanded or open dataset has not been proved yet. Could you show your...

01 March 2021 1,189 3 View

Amaury Lendasse Popular answer

Shannon's entropy can be used to measure Mutual Information between input and output variables. Also to detect outliers. I have worked on that topics but I don't know how it scales to Big Data...

Mutual information for the selection of relevant variables in spectrometric nonlinear modelling

DOI: 10.1016/j.chemolab.2005.06.010

https://www.researchgate.net/publication/1766203_Mutual_information_for_the_selection_of_relevant_variables_in_spectrometric_nonlinear_modelling

Article Mutual Information for the selection of relevant variables i...

Amaury Lendasse

Lukasz P Kozlowski

entropy can be used as one of the features during machine learning (I have seen many papers using it, sometimes I also use it), but it depends on particular problem whether it will bring any add value

Dr. Indrajit Mandal

Dear friend,

Its already being used in machine learning...

You just see my publications.

you will find the details...

From,

Dr.Indrajt Mandal

Abbe Mowshowitz

Shannon entropy has been used extensively to measure the complexity of finite graphs, and has been used in chemical graph theory for purposes of classification. A typical procedure is to determine a partition of graph elements (e.g., vertices or edges), construct a finite probability scheme in the obvious way, and apply Shannon's entropy function to the probability scheme. The key is determining a partition (relative to some structural property such as symmetry or path lengths), often a computationally hard problem. Big data would be more challenging unless there is some way of approximating a partition of graph elements.

interesting!