ML Data Distribution

ML Data Distribution.

In machine learning, data distribution refers to the way in which data points are distributed or spread out across a dataset.
The distribution of data in a dataset can have a significant impact on the performance of machine learning algorithms.
Data distribution can be characterized by several statistical measures, including mean, median, mode, standard deviation, and variance. These measures help to describe the tendency, spread, and shape of the data.