LightGBM is a highly efficient gradient boosting framework that stands out for its ability to handle categorical features natively, without the need for extensive preprocessing. This article explores how LightGBM processes categorical data, its advantages, and practical applications. Introduction to LightGBM LightGBM (Light Gradient Boosting Machine) is designed to be efficient and scalable, capable of … Read more
Random Forest is a versatile and powerful machine learning algorithm known for its robustness and ability to handle large datasets with high dimensionality. One of its key advantages is the ability to measure the importance of each feature in making predictions. Understanding feature importance helps in feature selection, model interpretation, and enhancing model performance. This … Read more
One of the most important factors that affect the model performance lies within feature engineering in the domain of machine learning. Data scientists and ML engineers go through trials and errors to refine these data points into meaningful features that fuel the predictive power of their models. From the selection of the most relevant features … Read more
