Cluster analysis or clustering is a statistical classification technique or activity that involves grouping a set of objects or data in such a way that those contained in the same group (cluster) will be similar to each other but different from those in the other group. It is required for data mining and exploration, and is commonly used in the bioinformatics industry and other sectors within the scope of machine learning, pattern recognition, image analysis, and analyzing large datasets.
Data governance ensures that your data is consistent, reliable, accurate, and trusted in data-driven retrieval processes.
Regression is a technique that studies the relationship between a dependent variable (outcome) and one or more independent variables (inputs) in the processes of statistical modeling and data analysis.
Latent Dirichlet Allocation (LDA) is a topic modeling technique that allows the discovery of hidden topic structures on large amounts of text data.
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