Time Series Clustering

This repository contains curated material for Time Series Clustering using Hierarchical-Based Clustering Method. The primary objective of this course is to provide a comprehensive implementation for time series clustering analysis to understand the process of grouping time series data into a similar pattern using the R programming language. The syllabus covers:

• Overview of Clustering

• Time Series Clustering

  • Data Collection
  • Preprocessing data time series
  • Exploratory Data Analysis
  • Distance Matrix
    • Euclidean Distance
    • Dynamic Time Warping

• Hierarchical Clustering

  • Agglomerative Nesting (AGNES)
    • Agglomerative Coefficient (AC)
    • Linkage
  • Divisive Analysis (DIANA)
    • Divisive Coefficient (DC)
  • Working with Dendrograms

• Determine Optimal Cluster

  • Scree plot
  • Silhouette

• Communicate insights for business needs