Data Analytics in Bioinformatics. Группа авторов
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*Corresponding author: [email protected]
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Introduction to Unsupervised Learning in Bioinformatics
Nancy Anurag Parasa1, Jaya Vinay Namgiri1, Sachi Nandan Mohanty2 and Jatindra Kumar Dash1*
1 Department of Computer Science and Engineering, SRM University-AP, Andhra Pradesh, Amaravathi, India
2 Department of Computer Science and Engineering, IcfaiTech, ICFAI Foundation for Higher Education, Hyderabad, India
*Corresponding author: [email protected]
Abstract
Unsupervised learning algorithmic techniques are applied in grouping the data depending upon similar attributes, most similar patterns, or relationships amongst the dataset points or values. These Machine learning models are also referred to as self-organizing models which operate on clustering technique. Distinct approaches are employed on every other algorithm in splitting up data into clusters. Unsupervised machine learning uncovers previously unknown patterns in data. Unsupervised machine learning algorithms are applied in case of data insufficiency. Few applications of unsupervised machine learning techniques include: Clustering, anomaly detection. Clustering