Open AccessJournal Article
k-Nearest Neighbor Classification Algorithm for Multiple Choice Sequential Sampling
TLDR
This work shows how the k-nearest neighbor classification algorithm in machine learning can be utilized as a mathemati- cal framework to derive a variety of novel sequential sampling models and proposes a common mathe- matical framework combining these methods and providing a systematic explanation for understanding different methods.About:
This article is published in Cognitive Science.The article was published on 2013-01-01 and is currently open access. It has received 4 citations till now. The article focuses on the topics: Sequential probability ratio test & Bayesian inference.read more
Citations
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Journal ArticleDOI
Impact of Different Data Types on Classifier Performance of Random Forest, Naïve Bayes, and K-Nearest Neighbors Algorithms
TL;DR: Random Forest and k-Nearest Neighbor are proved to be the best classifiers for any type of dataset and Naive Bayes can outperform other two algorithms if the feature variables are in a problem space and are independent.
Proceedings ArticleDOI
A kNN-based approach for the machine vision of character recognition of license plate numbers
Ana Riza F. Quiros,Rhen Anjerome Bedruz,Aaron Christian Uy,Alexander C. Abad,Argel A. Bandala,Elmer P. Dadios,Arvin H. Fernando +6 more
TL;DR: This research proposes to automate the plate recognition process by installing an IP camera on a road and analyzing the video-feed to capture the vehicles along that road and using a k nearest neighbors (kNN) algorithm.
Proceedings ArticleDOI
Critical Analysis of Machine Learning Based Approaches for Fraud Detection in Financial Transactions
TL;DR: Various machine-learning algorithms such as Bayesian Networks, Recurrent Neural Networks, Support Vector Machines, Fuzzy Logic, Hidden Markov Model, K-Means Clustering,K-Nearest Neighbor and their existing implementations on fraud detection domain will be discussed to find a better approach for a fraud detection system.
Proceedings ArticleDOI
A Novel Approach for the Screening and the Classification of Macular Ischemia Caused by Diabetic Retinopathy Disease Using Retinal Image Datasets
TL;DR: An automated system is proposed for the detection and the classification of the Macular Ischemia based on a graph trace method for automatic A/V (Arteries and Veins) classification by extracting the graph from the segmented vascular structure.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
A Theory of Memory Retrieval.
TL;DR: A theory of memory retrieval is developed and is shown to apply over a range of experimental paradigms, and it is noted that neural network models can be interfaced to the retrieval theory with little difficulty and that semantic memory models may benefit from such a retrieval scheme.
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The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks
Roger Ratcliff,Gail McKoon +1 more
TL;DR: The diffusion decision model is reviewed to show how it translates behavioral data accuracy, mean response times, and response time distributions into components of cognitive processing, including research in the domains of aging and neurophysiology.
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Toward a universal law of generalization for psychological science
TL;DR: A psychological space is established for any set of stimuli by determining metric distances between the stimuli such that the probability that a response learned to any stimulus will generalize to any other is an invariant monotonic function of the distance between them.
Journal ArticleDOI
The variable discharge of cortical neurons: implications for connectivity, computation, and information coding
TL;DR: It is suggested that quantities are represented as rate codes in ensembles of 50–100 neurons, which implies that single neurons perform simple algebra resembling averaging, and that more sophisticated computations arise by virtue of the anatomical convergence of novel combinations of inputs to the cortical column from external sources.