Knowledge discovery The non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data. Loss See Cost. Machine learning In Knowledge Discovery, machine learning is most commonly used to mean the application of induction algorithms, which is one step in the knowledge discovery process. This is similar to the definition of empirical learning or inductive learning in Readings in Machine Learning by Shavlik and Dietterich. The value for an attribute is not known or does not exist.
Some algorithms have problems dealing with missing values.
Model A structure and corresponding interpretation that summarizes or partially summarizes a set of data, for description or prediction. The use of a learned model. Model deployment usually denotes applying the model to real data. On-Line Analytical Processing. OLAP commonly uses intermediate data structures to store pre-calculated results on multidimensional data, allowing fast computations.