The purpose of data mining Generally speaking, data mining is a process of discovering patterns or relationships in a set of data. Data mining tasks include simplifying data by reducing noise, dimensionality or finding important variables and combinations. Among techniques in data mining we have clustering, classification, association analysis, anomaly detection, forecasting and predicting scores…

As a beginner to data science, I was very perplexed about the first steps in the data cleaning process. I found myself struggling with the concept of data wrangling, EDA or feature engineering. In an attempt to untie the knot, I have, therefore, taken a Udacity course where I came…

“One of the commonest problems in statistics is, given a series of observations Xj, xit…, xn, to find a function of these, tn(xltxit…, xn), which should provide an estimate of an unknown parameter 0.” — M. H. QUENOUILLE (2016) Problems with the process of estimating these unknown parameters are that…

How outliers can affect your model performance? “Observation which deviates so much from other observations as to arouse suspicion it was generated by a different mechanism” — Hawkins(1980) Cook’s distance and outliers? How can they relate to each other? In statistics, Cook’s distance (often referred to as Cook’s D) is a common measurement of a data point’s influence. It’s a way…