Outlier and Missing ValueMeta-knowledge is the knowledge of the meaning, background, connection, etc. of the data.
Meta-knowledge is difficult to surface in importance, so if you just look at Data Science from a distance, It may not be clear. Working with meta-knowledge is sobering.
If you have a deep understanding of meta-knowledge, the depth and breadth of your analysis will increase when you do multivariate analysis or data mining. When you get stuck in an analysis, it can help you break the deadlock. Data physics seeks to bring together metadata and meta-knowledge from a physical perspective.
Meta-knowledge is tacit knowledge. It's in someone's head, but not everyone knows. In addition, even people who have it in their heads may not be able to organize their knowledge well.
There are many ways to bring this knowledge to the surface in an organized way .
When meta knowledge takes the form of data, the number of things that can be analyzed increases dramatically. Dimensionality reduction analysis of time series data by R page is an example of shaping the data.
Meta knowledge that is managed as a type of data is called Meta Data.
NEXT Outlier and Missing Value
