Data Science based on R programming
About Lesson
  • Understanding the working of Kmeans Algorithm
  • Cluster Size Optimization vs Definition Optimization,
  • Hierarchical and non-hierarchical
  • K- medoid and Fuzzy K means
  • Case study for clustering
  • Hierarchical Clustering
  • k-Means algorithm for clustering – groupings of unlabeled data points.
  • Principal Component Analysis(PCA)- Data
  • Independent components analysis(ICA)
  • Anomaly Detection
  • Recommender System-collaborative filtering algorithm