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Questions related from Nabil Belgasmi
Can Genetic Algorithms (or GP) outperform Artificial Neural Networks? ANNs try build a "complex" mathematical function that best fits a given input to an output. This principle was used largely to...
10 October 2015 2,719 17 View
Recently, I was interested in the following topics: - Curve fitting - Periodicity detection - Pattern recognition - Genetic programming I found out that they can be connected to the Forecasting...
05 May 2015 3,029 17 View
During the supervised training phase, an ANN builds an approximated function that matches a list of inputs to a list of desired outputs. In the search phase of a genetic programming algorithm, a...
10 October 2013 6,486 91 View
What makes an ANN successful in generalizing its decision to non previously seen inputs? From a mathematical point of view, there are unlimited numbers of multi-dimensional functions that can fit...
10 October 2013 7,056 8 View
Artificial neural networks are well suited for prediction, forecasting, generalising decisions based on previously processed data, classifying data, building meta-models based on samples. In my...
09 September 2013 8,758 82 View
Assume we have two random variables: X and Y. We construct a 95%-confidence interval of the mean of X and Y. The two intervals are denoted: CI(X) and CI(Y). What is the statistical meaning of the...
08 August 2013 2,870 13 View
I would like to have a correct interpretation of the situation where two confidence intervals instances CI(X,Sx) and CI(Y,Sy) are overlapping. Sx and Sy refer to two samples sets of X and Y...
08 August 2013 10,019 13 View
PROBLEM FORMULATION AND ASSUMPTIONS ====================================== Let X and Y be two dependent random variables that are not necessarily Gaussian. mX and mY are their true means which...
08 August 2013 6,488 18 View
