Novel Convex Polyhedron Classifier for Sentiment Analysis
- Resource Type
- Authors
- Soufiane El Mrabtt; Hicham Omara; Mohamed Lazaar; Mohammed Al Achhab
- Source
- Cloudtech
- Subject
- Convex hull
0209 industrial biotechnology
business.industry
Computer science
Feature selection
Pattern recognition
02 engineering and technology
Statistical classification
020901 industrial engineering & automation
Hyperplane
Convex polytope
0202 electrical engineering, electronic engineering, information engineering
Piecewise
020201 artificial intelligence & image processing
Artificial intelligence
business
Classifier (UML)
Linear separability
- Language
In this paper, we propose a Novel Convex Polyhedron classifier (NCPC) based on the geometric concept convex hull. NCPC is basically a linear piecewise classifier (LPC). It partitions linearly non-separable data into various linearly separable subsets. For each of these subset of data, a linear hyperplane is used to classify them. We evaluate the performance of this classifier by combining it with two feature selection methods (Chi- squared and Anova F-value). Using two datasets, the results indicate that our proposed classifier outperforms other LPC- based classifiers.