Machine Learning (ML) models are increasingly being used to augment human decision making process in domains such as finance, telecommunication, healthcare, and others. In most of the cases, users do not understand how these models make predictions. The lack of understanding makes it difficult for policy makers to justify their decisions. Most of the ML models are black boxes that do not explain on its own why it reached a specific recommendation or a decision. This forces the users to say…Continue
Added by Janardhanan PS on February 27, 2020 at 7:00pm — No Comments
Why do we take logs of variable in Regression analysis?
We should remember that a regression equation has two parts
i) The Dependent variable (Predictand)
ii) The Independent variables (Predictors) ; which can be one or more and can be of different types (Categorical or Continuous).
The nature of the regression that we should run depends on the type of Dependent variable that we are dealing with in our model. For example, if the dependent variable is Continuous…Continue
Added by Sibashis Chakraborty on October 20, 2019 at 8:57am — No Comments
The covariance matrix has many interesting properties, and it can be found in mixture models, component analysis, Kalman filters, and more. Developing an intuition for how the covariance matrix operates is useful in understanding its practical implications. This article will focus on a few important properties, associated proofs, and then some interesting practical applications, i.e., extracting transformed polygons from a Gaussian mixture's covariance matrix.
I have often found that…Continue
Added by Rohan Kotwani on May 26, 2019 at 7:30am — No Comments
What a weird question. That’s what you would have thought after reading the headline. Perhaps you thought the word “NOT” was accidental.
Hmm, for past few years many of us have come across articles like
We all know models are always an illusion of reality - yet may or may not be useful. Data scientists should build both simple and complex models with reasonable and testable assumptions that capture what is…Continue
Added by Michael Walker on December 5, 2014 at 6:31pm — No Comments
Leonard Baum and Lloyd Welch designed a probabilistic modelling algorithm to detect patterns in Hidden Markov Processes. They built upon the theory of probabilistic functions of a …Continue
NFL 2013 Team Expected Points Added (EPA) per game - Defense by Offense
The atavistic love of sport, strategy,…Continue
Added by Michael Walker on January 27, 2014 at 7:00pm — No Comments
Added by Michael Walker on November 17, 2013 at 8:30am — No Comments
Natural language processing (NLP) involves machine learning, artificial intelligence, algorithms and linguistics related to interactions between computers and human languages. One important goal…Continue
Added by Michael Walker on August 20, 2013 at 7:27pm — No Comments
Ray Wang's HBR piece "What a Big-Data Business Model Looks Like" asserts three basic information…Continue
Added by Michael Walker on January 10, 2013 at 9:30am — No Comments