Assignment Week 2 Copy.docx Assignment University of The Cumberlands Intro to Data Mining What is knowledge discovery In databases (KDD)? Knowledge discovery in Databases is a thorough process of identifying th
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Assignment Week 2 Copy.docx Assignment University of The Cumberlands Intro to Data Mining What is knowledge discovery In databases (KDD)? Knowledge discovery in Databases is a thorough process of identifying the knowledge in the data and the identification process is performed through a very high-level application different datamining method. Multiple subjects like machine learning, statistics, Artificial Intelligence, Acquisition of knowledge for the expert systems, databases and visualization the data. As the goal is extract the knowledge from the data with related to large databases, it can be achieved by using few data mining methods to extract the knowledge with the specifications of perfect measures using database along with required subsampling, preprocessing and the transformations of the database. (Brownlee, J. 2020) Knowledge discovery in databases process integrating the data storage and access algorithms with the large data sets and then interpreting the results. It is a multi-steps process of understating the application domains involved, selecting the data sets, cleanse and preprocess the data and then simplify the data sets. Choosing the data mining algorithm will be the final step in the process that will help interpret important knowledge from the patterns that are mined. Review section 1.2 and review the various motivating challenges. Select one and note what it is and why it is a challenge. Data Mining face many challenges due to the new data sets and. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . .. .. . . . . . . . . . . . . . . . . . .. . . . .
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