Neural Networks and the Bias/Variance Dilemma

Maximum Likelihood from Incomplete Data Via the EM Algorithm

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Classification and Regression Trees.

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A novel Boosted-neural network ensemble for modeling multi-target regression problems

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Combining predictors: comparison of five meta machine learning methods

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Computing confidence intervals for stochastic simulation using neural network metamodels

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A Statistical Approach to Scanning the Biomedical Literature for Pharmacogenetics Knowledge

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Constrained cascade generalization of decision trees

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A Study on Bayes Feature Fusion for Image Classification

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A consistency-based model selection for one-class classification

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Modelling roach (Rutilus rutilus) microhabitat using linear and nonlinear techniques

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Prediction of the intern parameters tomato greenhouse in a semi-arid area using a time-series model of artificial neural networks

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Sparse Classifier Fusion for Speaker Verification

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Evaluating the Theoretic Adequacy and Applied Potential of Computational Models of the Spacing Effect

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Bias learning, knowledge sharing

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Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 3. Network Jacobians

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Classification of patients with pain based on neuropathic pain symptoms: Comparison of an artificial neural network against an established scoring system

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Call Availability Prediction in a Telecommunication System: A Data Driven Empirical Approach

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Predicting fish distribution in a mesotrophic lake by hydroacoustic survey and artificial neural networks

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A New Metric-Based Approach to Model Selection

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Design of robust neural network classifiers

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Practical application of machine learning on fast phase equilibrium calculations in compositional reservoir simulations

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Spatiotemporal Representation Learning for Blind Video Quality Assessment

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Leveling Down in Computer Vision: Pareto Inefficiencies in Fair Deep Classifiers

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Economic forecasting : challenges and neural network solutions

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Prediction and optimization of a ceramic casting process using a hierarchical hybrid system of neural networks and fuzzy logic

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Applications of neural network methods to the processing of earth observation satellite data

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Explaining consumer choice through neural networks: The stacked generalization approach

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Using bayesian priors to combine classifiers for adaptive filtering

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Performance and efficiency: recent advances in supervised learning

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Unsupervised recognition of individual tigers and snow leopards from their footprints

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Elucidating Model Inadequacies in a Cloud Parameterization by Use of an Ensemble-Based Calibration Framework

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An empirical investigation of bias and variance in time series forecasting: modeling considerations and error evaluation

Berardi, V. L., & Zhang, G. (2003) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2003.810601 · Cited by 44

Remarks on the Use of Multilayer Perceptrons for the Analysis of Chemical Sensor Array Data

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Modelling of microhabitat used by fish in natural and regulated flows in the river Garonne (France)

Reyjol, Y., Lim, P., Belaud, A., & Lek, S. (2001) · Ecological Modelling · doi:10.1016/s0304-3800(01)00301-5 · Cited by 45

Improving Supervised Learning by Feature Decomposition

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The Use of a Bayesian Neural Network Model for Classification Tasks

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Why bounded rationality (in epistemology)?

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Are rational actor models “rational” outside small worlds?

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Empirical models based on features ranking techniques for corporate financial distress prediction

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Regional forest-fire susceptibility analysis in central Portugal using a probabilistic ratings procedure and artificial neural network weights assignment

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Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment

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A neural network ensemble model for on-line monitoring of process mean and variance shifts in correlated processes

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Benchmarking of vertically-integrated CO2 flow simulations at the Sleipner Field, North Sea

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Considerations for selecting a machine learning technique for predicting deforestation

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A comparison between diatom-based pH inference models using Artificial Neural Networks (ANN), Weighted Averaging (WA) and Weighted Averaging Partial Least Squares (WA-PLS) regressions

Racca, J. M. J., Philibert, A., Racca, R., & Prairie, Y. T. (2001) · Journal of Paleolimnology · doi:10.1023/a:1012763829453 · Cited by 44

Wrapped input selection using multilayer perceptrons for repeat‐purchase modeling in direct marketing

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Critical heat flux prediction by using radial basis function and multilayer perceptron neural networks: A comparison study

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Effective Estimation of Posterior Probabilities: Explaining the Accuracy of Randomized Decision Tree Approaches

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Multiresolution learning paradigm and signal prediction

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Nonlinear modeling of scattered multivariate data and its application to shape change

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Decision Making: Nonrational Theories

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Classification in the Wild: The Science and Art of Transparent Decision Making

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Cognitive Science as a Source of Forward and Inverse Models of Human Decisions for Robotics and Control

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Economic policy uncertainty and bankruptcy filings

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Machine learning classification of CHIME fast radio bursts – I. Supervised methods

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Covariance-guided One-Class Support Vector Machine

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From perception to preference and on to inference: An approach–avoidance analysis of thresholds.

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Solar Irradiance Forecasting Using Dynamic Ensemble Selection

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A theory of neural computation with Clifford algebras

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Sparse Activity and Sparse Connectivity in Supervised LearningPreprint

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Performance and complementarity of two systemic models (reservoir and neural networks) used to simulate spring discharge and piezometry for a karst aquifer

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A neural network approach to category validation of Android applications

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A Comparison of Artificial Neural Networks and Multiple Regression in the Context of Research on Personality and Work Performance

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Rescuing Collective Wisdom when the Average Group Opinion Is Wrong

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Comparison between soft computing methods for tomato quality grading using machine vision

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Brain-Machine Interface Engineering

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Prediction of the gas–liquid volumetric mass transfer coefficients in surface-aeration and gas-inducing reactors using neural networks

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Linear decision rule as aspiration for simple decision heuristics

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Model Selection in Science: The Problem of Language Variance

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A cooperative ensemble learning system

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The pandemonium system of reflective agents

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A Machine Learning Approach to Price Indices: Applications in Commercial Real Estate

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Active Risk Estimation

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Semantic Image Networks for Human Action Recognition

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Input Selection Methods for Soft Sensor Design: A Survey

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Machine learning facilitated business intelligence (Part II)

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Defocus Blur Detection via Boosting Diversity of Deep Ensemble Networks

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Distance-based clustering challenges for unbiased benchmarking studies

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Marine Data Prediction: An Evaluation of Machine Learning, Deep Learning, and Statistical Predictive Models

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On selection of kernel parametes in relevance vector machines for hydrologic applications

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Nonstationarity and data preprocessing for neural network predictions of an economic time series

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Learning the Past Tense of English Verbs: The Symbolic Pattern Associator vs. Connectionist Models

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Active Learning for Open-set Annotation

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Estimating Escherichia coli loads in streams based on various physical, chemical, and biological factors

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A consistency-based model selection for one-class classification

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Review and comparative analysis of geometric semantic crossovers

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A SOM-based hybrid linear-neural model for short-term load forecasting

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Suspended sediment yield modeling in Mahanadi River, India by multi-objective optimization hybridizing artificial intelligence algorithms

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An accurate QSRR model for the prediction of the GC×GC–TOFMS retention time of polychlorinated biphenyl (PCB) congeners

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Spatial associative classification: propositional vs structural approach

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G-Protein Coupled Receptor Signaling Architecture of Mammalian Immune Cells

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An efficient multi-objective learning algorithm for RBF neural network

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Data mining applications in hydrocarbon exploration

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On the Selection of Weight Decay Parameter for Faulty Networks

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An alternative approach for investigation of the wave-induced scour around pipelines

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Forecasting chaotic cardiovascular time series with an adaptive slope multilayer perceptron neural network

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Combining Bias and Variance Reduction Techniques for Regression Trees

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An incremental learning algorithm that optimizes network size and sample size in one trial

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Small Data Can Play a Big Role in Chemical Discovery

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Retrieval of suspended sediment concentrations using remote sensing and machine learning methods: A case study of the lower Yellow River

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VIEW~~~~~~~~~~~~~~ ~ Communicated by Lawrence Jackel Neural Networks and the Bias/Variance Dilemma

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Neural Networks and the BiadVariance Dilemma

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VIEW Communicated by Lawrence Jackel Neural Networks and the BiadVariance Dilemma

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Neural networks and nonparametric regression

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