Low bias histogram-based estimation of mutual information for feature selection

Hacine-Gharbi, Abdenour; Ravier, Philippe; Harba, Rachid; Mohamadi, Tayeb

doi:10.1016/j.patrec.2012.02.022

Cited by 40 publications

(26 citation statements)

References 16 publications

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“…As one of the methods to compute I(τ), the histogram-based MI estimation divides the [31]. k x is the number of cells, and it is selected by…”

Section: Phase Space Reconstruction (Psr)mentioning

confidence: 99%

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Soft Measurement Modeling Based on Chaos Theory for Biochemical Oxygen Demand (BOD)

Qiao

2016

Water

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Abstract:The precision of soft measurement for biochemical oxygen demand (BOD) is always restricted due to various factors in the wastewater treatment plant (WWTP). To solve this problem, a new soft measurement modeling method based on chaos theory is proposed and is applied to BOD measurement in this paper. Phase space reconstruction (PSR) based on Takens embedding theorem is used to extract more information from the limited datasets of the chaotic system. The WWTP is first testified as a chaotic system by the correlation dimension (D), the largest Lyapunov exponents (λ 1 ), the Kolmogorov entropy (K) of the BOD and other water quality parameters time series. Multivariate chaotic time series modeling method with principal component analysis (PCA) and artificial neural network (ANN) is then adopted to estimate the value of the effluent BOD. Simulation results show that the proposed approach has higher accuracy and better prediction ability than the corresponding modeling approaches not based on chaos theory.

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“…As one of the methods to compute I(τ), the histogram-based MI estimation divides the [31]. k x is the number of cells, and it is selected by…”

Section: Phase Space Reconstruction (Psr)mentioning

confidence: 99%

“…Equations (9) and (10) are defined in reference [31] which has demonstrated that the method to choose k x can obtain more accurate MI.…”

Section: Phase Space Reconstruction (Psr)mentioning

confidence: 99%

Soft Measurement Modeling Based on Chaos Theory for Biochemical Oxygen Demand (BOD)

Qiao

2016

Water

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show abstract

“…The common methods to calculate MI include copula entropy method [32], Kernel method [33], k-nearest neighbor method [34] and histogram method [35,36]. In this paper, we adopt histogram method to estimate MI because it is the fastest and simplest method among them.…”

Section: Mutual Information Estimation Of Sfnnmentioning

confidence: 99%

Mutual information based weight initialization method for sigmoidal feedforward neural networks

Qiao

2016

Neurocomputing

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“…Currently, the commonly used MI estimators include histogram method [28], kernel method [29], k-nearest neighbor method [30], etc. Every MI estimator has its advantages and scope of applications.…”

Section: Mutual Informationmentioning

confidence: 99%

Global mutual information-based feature selection approach using single-objective and multi-objective optimization

Han

Ren

2015

Neurocomputing

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Low bias histogram-based estimation of mutual information for feature selection

Cited by 40 publications

References 16 publications

Soft Measurement Modeling Based on Chaos Theory for Biochemical Oxygen Demand (BOD)

Soft Measurement Modeling Based on Chaos Theory for Biochemical Oxygen Demand (BOD)

Mutual information based weight initialization method for sigmoidal feedforward neural networks

Global mutual information-based feature selection approach using single-objective and multi-objective optimization

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