Feature Engineering and Selection for Regression Models with Python and Scikit-learn
Training a machine learning model is like baking a cake: the quality of the end result depends on the ingredients … Read more
Feature Exploration
Feature exploration is the process of analyzing and understanding the different features or attributes of a data set in order to gain insights and inform the development of machine learning models. This process typically involves visualizing the data and looking for patterns and relationships between the different features, as well as performing statistical analysis to identify trends and outliers. Feature exploration is an important step in the machine learning process, as it can help to identify the most important or relevant features to include in the model, and can help to ensure that the model is well-suited to the problem at hand.