Time Series Clustering

Time series clustering is a method used to group sequences of data points—like stock prices or weather patterns—that change over time. By analyzing the patterns within these sequences, it identifies which series are similar, helping to reveal shared behaviors or trends. For example, it can group cities with similar temperature fluctuations over a year. This process allows organizations to understand complex temporal data better, make predictions, or identify common factors, all by organizing similar time-based data into meaningful clusters for easier analysis and decision-making.