Gain more knowledge in regexp with stringR — Introduction When a project involves text analysis, such as sentiment analysis, text mining, or any other task you were entitled to do analyzing textual information will probably require parsing text at some point. …

Aprenda os passos básicos para rodar uma AnaCor no R. Introdução Datasets são feitos de números e/ou texto. Logo, espera-se que nem todas as variáveis sejam apenas números, os quais, por sua vez, contam com muitas técnicas para serem analisados, testados e trabalhados. Quando estamos trabalhando com variáveis numéricas, existem ferramentas…

Learn the basic steps to run a Multiple Correspondence Analysis in R — Introduction Datasets are made of numbers and/ or text. Thus, we should expect that not all the variables will be just about numbers, which, by the way, count on many techniques to be analyzed, tested and worked. When we are working with numerical variables, there are tools like correlation, PCA, scaling…

It is easy to return more than a Boolean list. When you’re using Scikit Learn’s SelectKBest, you are interested in returning the k best features for you model. …

Tweak your model to classify only with a higher degree of certainty — Introduction When creating a classification model, many algorithms offer the function predict_proba() to give us the probability of that observation being classified under each class. Thus, it is common to see an output like this: [0.925, 0.075] In the previous case, the model is 92.5% sure that the observation pertains to…

If you got to this post it is probably because of the controversial fame of Regular Expressions, or just RegEx for short… But what are those? Well, regex is an encoded expression — or a sequence of characters — used to match any kind of patterns in a string. …

I have created a model to predict the outcome of the FIFA World Cup games — We are now one week deep into the FIFA World Cup 2022. More than 20 games have already occurred with some pretty “predictable” results, as well as some surprises, what is somewhat not uncommon in football (or soccer, whatever you want to call it). A couple of days before the…

A simple technique to One-Hot Encode variables using Pandas — Introduction Data cleaning is necessary. I believe most of us agree on that. A project will usually begin with some exploration and cleaning before we can go to the modeling part. Actually, I would say that most of a Data Scientist’s work is done between cleaning and transforming the dataset. The…

Two options: Local Outlier Factor and Gaussian Mixture Models — Introduction Outliers are a frequently discussed subject in many Data Science forums and blogs. This is probably because these data points can distort our analysis and can affect the modeling, if the algorithm we’re using is not robust to those anomalies. A dataset, many times, will bring the majority of the…