Communications of the ACM
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Constructing hidden units using examples and queries
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Generalizing from case studies: a case study
ML92 Proceedings of the ninth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Initializing back propagation networks with prototypes
Neural Networks
Dynamic cell structure learns perfectly topology preserving map
Neural Computation
The nature of statistical learning theory
The nature of statistical learning theory
Global Optimization for Neural Network Training
Computer - Special issue: neural computing: companion issue to Spring 1996 IEEE Computational Science & Engineering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hybrid learning schemes for fast training of feed-forward neural networks
Mathematics and Computers in Simulation - Special issue: signal processing and neural networks
Mathematical reflections: in a room with many mirrors
Mathematical reflections: in a room with many mirrors
2D spiral pattern recognition with possibilistic measures
Pattern Recognition Letters
Centroid based Multilayer Perceptron Networks
Neural Processing Letters
Least Squares Support Vector Machine Classifiers
Neural Processing Letters
Accelerating neural network training using weight extrapolations
Neural Networks
Applying SP-MLP to complex classification problems
Pattern Recognition Letters
Determining the number of centroids for CMLP network
Neural Networks
Learning in Neural Networks: Theoretical Foundations
Learning in Neural Networks: Theoretical Foundations
Hybrid Feedforward Neural Networks for Solving Classification Problems
Neural Processing Letters
Hierarchical neuro-fuzzy quadtree models
Fuzzy Sets and Systems - Fuzzy models
Opposites Attract: Complementary Phenotype Selection for Crossover in Genetic Programming
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
Extending and Benchmarking the CasPer Algorithm
AI '97 Proceedings of the 10th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
A Cascade Network Algorithm Employing Progressive RPROP
IWANN '97 Proceedings of the International Work-Conference on Artificial and Natural Neural Networks: Biological and Artificial Computation: From Neuroscience to Technology
Artificial Neural Networks with Adaptive Multidimensional Spline Activation Functions
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
Hybrid nets with variable parameters: a novel approach to fast learning under backpropagation
INBS '95 Proceedings of the First International Symposium on Intelligence in Neural and Biological Systems (INBS'95)
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
A functions localized neural network with branch gates
Neural Networks
Perceptrons: An Introduction to Computational Geometry
Perceptrons: An Introduction to Computational Geometry
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
On Growing Self - Organizing Neural Networks without Fixed Dimensionality
CIMCA '06 Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce
Rectified nearest feature line segment for pattern classification
Pattern Recognition
A hybrid neural network model for noisy data regression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy perceptron neural networks for classifiers with numerical data and linguistic rules as inputs
IEEE Transactions on Fuzzy Systems
Support vector learning mechanism for fuzzy rule-based modeling: a new approach
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Information Theory
The pandemonium system of reflective agents
IEEE Transactions on Neural Networks
The cascade-correlation learning: a projection pursuit learning perspective
IEEE Transactions on Neural Networks
Automated learning for reducing the configuration of a feedforward neural network
IEEE Transactions on Neural Networks
Circular backpropagation networks for classification
IEEE Transactions on Neural Networks
Kernel orthonormalization in radial basis function neural networks
IEEE Transactions on Neural Networks
CARVE-a constructive algorithm for real-valued examples
IEEE Transactions on Neural Networks
Representation and generalization properties of class-entropy networks
IEEE Transactions on Neural Networks
Training multilayer perceptron classifiers based on a modified support vector method
IEEE Transactions on Neural Networks
A geometrical representation of McCulloch-Pitts neural model and its applications
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Exploring constructive cascade networks
IEEE Transactions on Neural Networks
SEPARATE: a machine learning method based on semi-global partitions
IEEE Transactions on Neural Networks
Divide-and-conquer learning and modular perceptron networks
IEEE Transactions on Neural Networks
Perceiving geometric patterns: from spirals to inside-outside relations
IEEE Transactions on Neural Networks
Constructive feedforward ART clustering networks. II
IEEE Transactions on Neural Networks
Fully automatic clustering system
IEEE Transactions on Neural Networks
A fuzzy ARTMAP nonparametric probability estimator for nonstationary pattern recognition problems
IEEE Transactions on Neural Networks
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The two-spiral task is a well-known benchmark for binary classification. The data consist of points on two intertwined spirals which cannot be linearly separated. This article reviews how this task and some of its variations have significantly inspired the development of several important methods in the history of artificial neural networks. The two-spiral task became popular for several different reasons: (1) it was regarded as extremely challenging; (2) it belonged to a suite of standard benchmark tasks; and (3) it had visual appeal and was convenient to use in pilot studies. The article also presents an example which demonstrates how small variations of the two-spiral task such as relative rotations of the two spirals can lead to qualitatively different generalisation results.