June 2020
Intermediate to advanced
382 pages
11h 39m
English
To understand the role of unsupervised learning, it is important to first look at the overall life cycle of the data-mining process. There are different methodologies that divide the life cycle of the data-mining process into different independent stages, called phases. Currently, there are two popular ways to represent the data-mining life cycle:
CRISP-DM (Cross-Industry Standard Process for Data Mining) life cycle
SEMMA (Sample, Explore, Modify, Model, Access) data-mining process
CRISP-DM was developed by a consortium of data miners who belonged to various companies, including Chrysler and SPSS (Statistical Package for Social Science). SEMMA was proposed by SAS (Statistical Analysis ...