Supervised Learning Archives

Buridan's donkey at an equal distance from hay and water

April 12, 2023 Machine Learning

k-Nearest Neighbors (k-NN) – A Man is Known by the Company He Keeps

Aesop was a Greek storyteller who created lots of short stories more than 2500 years ago (such as the hare and the tortoise), now collectively known as Aesop’s Fables. "A man is known by the company he keeps" is a quote also attributed to him that has survived through the ages and has proven to be a timeless truth. The k-Nearest Neighbors (k-NN) algorithm is essentially based on the same idea. It suggests that when a machine needs to classify a new data point in an application, examining its neighboring data points is an effective strategy. In the spirit of

Decision boundary for multivariate logistic regression

August 9, 2022 Machine Learning

Logistic Regression in Machine Learning

A hundred thousand years ago, our ancestors used to roam in the savannas and jungles. It was absolutely necessary for them to judge (or classify) everything they encounter: a movement in the bushes could be due to a harmless rabbit or a dangerous tiger, a fruit on a plant could be nutritious or poisonous, and so on. Then came the wizards who invented language and then people developed agriculture, writing and industry. The advancement in civilization and the quest for scientific knowledge revealed the benefits of a wide spectrum and viewing shades of gray instead of of simple black and

February 13, 2021 Machine Learning

Machine Learning – The Big Picture

Machine learning is probably the defining technology of the past decade. As with all walks of life, it is playing an increasingly significant role in existing and future wireless networks. In this article, we explore the big picture of this exciting field. Nature vs Man Humans have always been interested in the workings of a mind, replicated by machines in many science fiction stories. During their investigations on Artificial Intelligence (AI, of which machine learning is a subset), many scientists observed that the machines need not copy the exact brain but a functional level performance is good enough that can