Recent advances on optimum-path forest for data classification: supervised, semi-supervised and unsupervised learning
نویسندگان
چکیده
Although one can find several pattern recognition techniques out there, there is still room for improvements and new approaches. In this book chapter, we revisited the Optimum-Path Forest (OPF) classifier, which has been evaluated over the last years in a number of applications that consider supervised, semi-supervised and unsupervised learning problems. We also presented a brief compilation of a number of previous works that employed OPF in different research fields, that range from remote sensing image classification to medical data analysis.
منابع مشابه
Semi-Supervised Learning Based Prediction of Musculoskeletal Disorder Risk
This study explores a semi-supervised classification approach using random forest as a base classifier to classify the low-back disorders (LBDs) risk associated with the industrial jobs. Semi-supervised classification approach uses unlabeled data together with the small number of labelled data to create a better classifier. The results obtained by the proposed approach are compared with those o...
متن کاملEnsemble learning with trees and rules: Supervised, semi-supervised, unsupervised
In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised, semi-supervised and unsupervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by post processing the rules with partial least squares regression have significantly better prediction performance than ...
متن کاملWised Semi-Supervised Cluster Ensemble Selection: A New Framework for Selecting and Combing Multiple Partitions Based on Prior knowledge
The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...
متن کاملDesign of Pattern Classifiers Using Optimum-Path Forest with Applications in Image Analysis
Current image acquisition and storage technologies have provided large data sets (with millions of samples) for analysis. Samples may be images from an image database, objects extracted from several images, or image pixels. This scenario is very challenging for traditional machine learning and pattern recognition techniques, which need to be more efficient and effective in large data sets. This...
متن کاملWised Semi-Supervised Cluster Ensemble Selection: A New Framework for Selecting and Combing Multiple Partitions Based on Prior knowledge
The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...
متن کامل