Outlier Detection in High Dimensional Data
Anusha L1, Nagaraja G S2
1Anusha L*, Student, Department of Computer Science and Engineering, Rashtreeya Vidyalaya college of Engineering, Bengaluru, (Karnataka), India.
2Dr. Nagaraja G S, Professor and Associate Dean, Department of Computer Science and Engineering, Rashtreeya Vidyalaya College of Engineering, Bengaluru (Karnataka), India.
Manuscript received on May 21, 2021. | Revised Manuscript received on May 10, 2021. | Manuscript published on June 30, 2021. | PP: 37-42 | Volume-10 Issue-5, June 2021. | Retrieval Number: 100.1/ijeat.E26750610521 | DOI: 10.35940/ijeat.E2675.0610521
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Artificial intelligence (AI) is the science that allows computers to replicate human intelligence in areas such as decision-making, text processing, visual perception. Artificial Intelligence is the broader field that contains several subfields such as machine learning, robotics, and computer vision. Machine Learning is a branch of Artificial Intelligence that allows a machine to learn and improve at a task over time. Deep Learning is a subset of machine learning that makes use of deep artificial neural networks for training. The paper proposed on outlier detection for multivariate high dimensional data for Autoencoder unsupervised model.
Keywords: Outlier Detection, Autoencoder Model, Unsupervised Model.
Scope of the Article: Artificial Intelligence