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Letter Recognition Using Holland-Style Adaptive Classifiers

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A Learning Algorithm for Boltzmann Machines**The research reported here was supported by grants from the System Development Foundation. We thank Peter Brown, Francis Crick, Mark Derthick, Scott Fahlman, Jerry Feldman, Stuart Geman, Gail Gong, John Hopfield, Jay McClelland, Barak Pearlmutter, Harry…
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Induction

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Squeezing the last drop: Cluster-based classification algorithm
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Learning handwriting by evolution: a conceptual framework for performance evaluation and tuning
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An improved branch and bound algorithm for feature selection
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Formal methods in pattern recognition: A review
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Self-Organizing Neural Networks for Stable Control of Autonomous Behavior in A Changing World
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Self-organizing maps for outlier detection
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Case-based reasoning in IVF: prediction and knowledge mining
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Software diversity: practical statistics for its measurement and exploitation
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Capturing perceptual expertise: a sound equalization expert system
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Coevolving functions in genetic programming
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Automatic model selection in a hybrid perceptron/radial network
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Technical Note: First Nearest Neighbor Classification on Frey and Slate's Letter Recognition Problem
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Selective Sampling for Nearest Neighbor Classifiers
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Multivariate Density Estimation by Bayesian Sequential Partitioning
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A new oscillating-error technique for classifiers
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The discrimination power of projection pursuit with different density estimators
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The Construction of a Majority-Voting Ensemble Based on the Interrelation and Amount of Information of Features
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Less is more: simple algorithms for the minimum sum of squares clustering problem
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Pattern fusion in feature recognition neural networks for handwritten character recognition
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A self-organizing neural network for supervised learning, recognition, and prediction
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Theoretical and practical considerations of uncertainty and complexity in automated knowledge acquisition
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Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps
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Decision-based neural networks with signal/image classification applications
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Progress on Artificial Neural Networks for Big Data Analytics: A Survey
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Why Is Multiclass Classification Hard?
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Topological Forest
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SS-DBSCAN: Semi-Supervised Density-Based Spatial Clustering of Applications With Noise for Meaningful Clustering in Diverse Density Data
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Script independent scene text segmentation using fast stroke width transform and GrabCut
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Distributed forests for MapReduce-based machine learning
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Robust bidding in LCS using loan and bid history
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A new bidding strategy in LCS using a decentralized loaning and bid history
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Fiducial marker indoor localization with Artificial Neural Network
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Compact multi-class boosted trees
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High-performance geometric algorithms for sparse computation in big data analytics
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IFGAN: Missing Value Imputation using Feature-specific Generative Adversarial Networks
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Benchmark of Data Preprocessing Methods for Imbalanced Classification
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Toward a high-performance clustering algorithm for securing edge computing environments
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Enhanced prediction of protein cellular localization sites with genetic algorithm optimal kernel projection analysis
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Using an ICA representation of high dimensional data for object recognition and classification
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Optimizing 1-Nearest Prototype Classifiers
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Stochastic Computing co-processing elements for Evolving Autonomous Data Partitioning
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A computational model for grounding words in the perception of agents
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Residual Networks Behave Like Boosting Algorithms
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Multi-instance Multi-label Learning Based on Parallel Attention and Local Label Manifold Correlation
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Training techniques to obtain fault-tolerant neural networks
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ParaFIS:A new online fuzzy inference system based on parallel drift anticipation
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A Kind of Fuzzily Combinative Classifiers for Solving Large-Scale Learning Problems
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Fuzzily Modular Multilayer Perceptron Classifiers for Large-Scale Learning Problems
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Fuzzily modular single-layer RBF neural networks for solving large-scale classification problems
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Fuzzy clustering with Learnable Cluster dependent Kernels
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Transformation of discriminative single-task classification into generative multi-task classification in machine learning context
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Scalable Kernel Learning Via the Discriminant Information
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Using OCR to automate document conversion to LATEX
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