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  1. Proceedings of the International Conference on Artificial Intelligence and Robotics and the International Conference on Automation, Control and Robotics Engineering (ICAIR-CACRE '16)
  2. Indexing rules in rule sets for fast classification
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A method for industrial robot manipulators trajectory planning based on piecewise continuous function
Prandtl-Ishlinskii model-based adaptive feedforward control for piezoelectric-stack-actuator-driven systems
LSTSRS-SVM applied in large scale wireless sensor networks localization
Tooth contact analysis and assembly error analysis of a helical gear speed reducer with linear tip-relief
Collision avoidance path planning for the 6-DOF robotic manipulator
An adaptive Smith Predictor control scheme for a downstream vacuum system
Learning to prioritize GUI test cases for Android laboratory programs
Development of LCD-based additive manufacturing system for biomedical application
Obstacle avoidance path planning of free-floating space manipulator for on-orbit observation
Consensus speed maximisation in engineered swarms with autocratic leaders
The method of multi-step dimensionality reduction and parallel feature fusion in clothing recognition
Analysis of an intruder detection probability for a mobile sensor network in a belt region
A system for an anticipative front human following robot
Development of holistic corner control for electric vehicle using a new driver command interpreter
Road detection algorithm of integrating region and edge information
A harmonic canceller for hydraulic servo seismic system based on the parallel filtered-X adaptive notch filter
Walking synchronously with a mobile robot using mutual rhythmic entrainement
A new approach of shift schedule optimization for AMT vehicle based on optimal theory
Hierarchical boosting for transfer learning with multi-source
CAD/CAE of spherical gears
Indexing rules in rule sets for fast classification
A new approach to identify the ball screw wear based on feed motor current
An improved computational framework using one stage filtration by incorporating knowledge in gene expression clustering
Benchmark of feature selection techniques with machine learning algorithms for cancer datasets
Learning sensorimotor navigation using synchrony-based partner selection
Image completion with variable scope patch sampling

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Indexing rules in rule sets for fast classification

Content Provider ACM Digital Library
Author Lindgren, Tony
Abstract Using sets of rules for classification of examples usually involves checking a number of conditions to see if they hold or not. If the rule set is large the time to make the classification can be lengthy. In this paper we propose an indexing algorithm to decrease the classification time when dealing with large rule sets. Unordered rule sets have a high time complexity when conducting classification; we hence conduct experiments comparing our novel indexing algorithm with the standard way of classifying ensembles of unordered rule sets. The result of the experiment shows decreased classification times for the novel method that are ranging from 0.6 to 0.8 of that of the standard approach averaged over all experimental datasets. This time gain is obtained while retaining an accuracy ranging from 0.84 to 0.99 with regard to the standard classification method. The index bit size used with the indexing algorithm influence both the classification accuracy and time needed for conducting the classification task.
Starting Page 1
Ending Page 6
Page Count 6
File Format PDF
ISBN 9781450342353
DOI 10.1145/2952744.2952750
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2016-07-13
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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