Clustering using machine learning
In machine learning, clustering deals with identifying patterns or structures within uncategorized data without needing any external guidance. Clustering algorithms parse given data to identify clusters or groups with matching patterns that exist in the dataset. The result of clustering algorithms are clusters of data that can be defined as a collection of objects that are similar in a certain way. The following diagram illustrates how clustering works:
Figure 8.1 – Clustering
In the previous diagram, an uncategorized dataset is being passed through a clustering algorithm, resulting in the data being categorized into smaller clusters or groups of data, based on a data point's proximity to another data point in a two-dimensional Euclidian space.
Thus, the clustering algorithm groups data based on the Euclidean distance between the data on a two-dimensional plane. Clustering algorithms consider the Euclidean distance...
