A study of the ISOMAP algorithm and its applications in machine learning - David, Lucas Oliveira (Universidade Federal de São Carlos, 2015)
This project aims to study the foundations of nonlinear dimensionality reduction through manifold learning with the algorithm known as Isometric Feature Mapping (ISOMAP) and observe the application of the algorithm in practical experiments. The experiments were developed and executed in the following computational environment: Intel Core i7-4700MQ CPU 2.40GHz × 8, 16 GB of RAM. All the artifacts, (e.g., source-code, docs, experiments) can be found in the repository https://github.com/lucasdavid/manifold-learning and are licensed under the MIT License.
Um estudo do algoritmo ISOMAP e suas aplicações em aprendizado de máquina
Keywords: Machine learning; Dimensionality reduction; Manifold learning; Aprendizado de máquina; Redução de dimensionalidade; Aprendizado de manifolds; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::MATEMATICA DA COMPUTACAO