data cleaning Automatic data types checking in predictive models Given certain data, and we need to create models (xgboost, random forest, regression, etc). Each one of them has its constraints regarding data types. Errors are not clear, here's a new function to speed up model creation.
data preparation Fast data exploration for predictive modeling Before predictive model creation, we need to check/change numerical, categorical, NAs, one unique value and high cardinality variables. This new function will assist us in this task.
machine learning How to use `recipes` package from `tidymodels` for one hot encoding 🛠 Quick introduction to `recipes` package, from the `tidymodels` family, based on one hot encoding. Useful to automatize some data preparation tasks.
data preparation New discretization method: Recursive information gain ratio maximization This method can discretize a variable taking into consideration the target variable, similar to what decision tree do but with gain ratio.
rstats Exploratory Data Analysis & Data Preparation with 'funModeling' funModeling quick-start This package contains a set of functions related to exploratory data analysis, data preparation, and model performance. It is used by people coming from business, research, and teaching (professors and students)
rstats Data discretization made easy with funModeling tl;dr: Convert numerical variables into categorical, as it is shown in the next image. ⏳ Reading time ~ 6 min. Let's start! The package funModeling (from version > 1.6.6) introduces two functions—