Data analytics, statistics, and more
This post compares simple linear regression and multiple linear regression with and without shrinkage using an indoor air dataset consisting of trichloroethene concentrations and various explanatory variables, including radon concentration, temperature, barometric pressure, wind direction, and wind speed
This post explores linear regression with one-hot encoding. For those datasets with many categorical variables and where the categorical variables in turn have many unique levels, the number of features can quickly escalate. In these cases, label/ordinal encoding or some other alternative should be explored.
With the rapid spread in the novel coronavirus across countries, the World Health Organisation and several countries have published latest results on the impact of COVID-19 over the past few months. The objective of this post is to demonstrate how visualization using the R programmin language helps to derive informative insights from data sources.
This is a perfunctory exploration of the early transmission dynamics of coronavirus disease 2019 (COVID-19) in mainland China. The basic reproduction number and the per day infection mortality and recovery rates are estimated using a classic SIR compartmental model of communicable disease outbreaks.
Feature Selection is a core concept in machine (statistical) learning that can have significant impacts on model performance. This post examines various methods to identify the most important predictor variables in machine learning that explain the variance of the response variable.