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Evaluation of Neural Network Models with Generalized Sensitivity Analysis

https://doi.org/10.1021/ac0004963
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Outgoing claims: the papers this work cites, builds on, or argues with.

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Chemometrical treatment of electronic structures of 28 flavonoid derivatives
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Variable selection for neural networks in multivariate calibration
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Using input parameter influences to support the decisions of feedforward neural networks
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Temperature-Constrained Cascade Correlation Networks
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Automated Descriptor Selection for Quantitative Structure-Activity Relationships Using Generalized Simulated Annealing
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Knowledge Extraction from Transducer Neural Networks
inferredcites →https://doi.org/10.1080/00207729508929062openalex-snapshot
Stochastic sensitivity analysis method for neural network learning
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Data Mining of Inputs: Analysing Magnitude and Functional Measures

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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Bootstrap classification and point-based feature selection from age-staged mouse cerebellum tissues of matrix assisted laser desorption/ionization mass spectra using a fuzzy rule-building expert system
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Validation using sensitivity and target transform factor analyses of neural network models for classifying bacteria from mass spectra
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Sensitivity for Multivariate Calibration Based on Multilayer Perceptron Artificial Neural Networks
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Deep-Learning-Assisted Inverse Design of Chiral Metasurfaces With Dual-Band Circular Dichroism
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Sensitivity of Raman Spectra to Chemical Functional Groups
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Atmospheric particulate matter characterization by Fourier transform infrared spectroscopy: a review of statistical calibration strategies for carbonaceous aerosol quantification in US measurement networks
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