by Sole | Nov 6, 2023 | Feature Selection, Machine Learning, Python
Imagine you’re working with a large dataset, and you want to train a machine learning algorithm. The challenge lies in deciding which features from the myriad of variables should be considered to build an effective model. This is where feature selection comes... 
by Sole | Nov 6, 2023 | Feature Selection, Machine Learning, Python
Imagine you’re preparing a delicious cake for Christmas. You have a pantry full of ingredients, but you don’t know the perfect recipe. Would you throw everything into the pot? Probably not! You’d select the ingredients that make your dish taste the best.... 
by Sole | May 25, 2023 | Feature Selection, Interpretability, Machine Learning, Python
Feature importance plays a crucial role in the field of machine learning, as it allows us to identify and prioritize the most important features that contribute to the predictive power of our models. Feature importance is used to understand our model’s predictions and... 
by Sole | May 23, 2023 | Feature Selection, Machine Learning, Python
In machine learning, feature selection and feature importance play pivotal roles in constructing accurate and efficient predictive models. These concepts are essential for optimizing model performance, reducing dimensionality, enhancing interpretability, and improving... 
by Sole | Sep 11, 2022 | Feature Selection, Machine Learning, Python
An essential step in any data science project is to select the most predictive variables. There are various methods of feature selection. Some scale well but consider only features individually. Some are extremely computationally costly and thus applicable only to... 
by Sole | Aug 16, 2022 | Feature Selection, Machine Learning, Python
Recursive feature elimination (RFE) is the process of selecting features sequentially, in which features are removed one at a time, or a few at a time, iteration after iteration. Given a machine learning model, the goal of recursive feature elimination is to select...