How to do feature engineering with categorical data in R

Purpose: Machine learning models have difficulty interpreting categorical data; feature engineering allows us to re-contextualize our categorical data to improve the rigor of our machine learning models. Feature engineering also provides added layers of perspective to data analysis. The big question that feature engineering approaches solve is; how to I utilize my data in interesting …

Principal Component Analysis in R

Hi there! Welcome to my blog on pricipal component analysis in R. Purpose: PCA is a dimensionality rediction technique; meaning that each additional variable you’re including in your modeling process represents a dimension. What does it do?: In terms of what PCA actually does, it takes a dataset with high dimensionality, and reduces them down …