An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Feature Selection for Knowledge Discovery and Data Mining
Feature Selection for Knowledge Discovery and Data Mining
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
YALE: rapid prototyping for complex data mining tasks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Word segmentation of handwritten text using supervised classification techniques
Applied Soft Computing
Text classification: A least square support vector machine approach
Applied Soft Computing
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
Dynamic classification for video stream using support vector machine
Applied Soft Computing
Applied Soft Computing
Patent classification system using a new hybrid genetic algorithm support vector machine
Applied Soft Computing
Online signature verification with support vector machines based on LCSS kernel functions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on gait analysis
An overview of statistical learning theory
IEEE Transactions on Neural Networks
A hybrid expert system approach for telemonitoring of vocal fold pathology
Applied Soft Computing
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Handedness is a certain kind of laterality, namely the preference of humans for a certain hand (the dominant hand). Reliable handedness tests are needed in various contexts, for example, to avoid a wrong writing education of children. In this article, we propose a new approach for a gradual rating of hand proficiency which consists of three subtests and is suited for preschool children. We demonstrate the benefits of using a graphics tablet for handedness tests, investigate the advantages of the three subtests and their combination, and outline the possibility of interpreting the gradual output of a classifier. The classification is based on ensembles of support vector machines that are trained with sample data. Input of these classifiers are attributes that reflect various aspects of hand motor skills. The most relevant input attributes of the classifiers are selected from a large set of possible attributes with a ranking technique based on the Gini index. We evaluate this approach using a data set with data gathered from 53 preschool children aged between five and six and a half (45 with certain and known handedness, 8 with uncertain or ambiguous handedness).