• Home
  • Contact
Menu
  • Home
  • Contact

Category: unsupervised

Hierarchical Clustering

  • August 5, 2019June 27, 2021
  • by Niranjan B Subramanian

Hierarchical clustering is the second most popular technique for clustering after K-means.  Remember, in K-means; we need to define the number of clusters beforehand. However, in hierarchical clustering, we don’t have to specify the number of […]

Continue readingMore Tag

Introduction to K-means

  • July 11, 2019June 27, 2021
  • by Niranjan B Subramanian

K-means clustering is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. Before we venture into K-means, let’s first understand what clustering is? What is clustering? The idea behind clustering is […]

Continue readingMore Tag

Introduction to Principal Component Analysis(PCA)

  • May 22, 2019June 27, 2021
  • by Niranjan B Subramanian

Principal Component Analysis is an unsupervised dimensionality reduction technique, which is extensively used in machine learning. It helps us to alleviate the problem of the curse of dimensionality by reducing the dimension of the data. PCA […]

Continue readingMore Tag

Copyright © 2019 AI ASPIRANT | All Rights Reserved.