Linear regression is a supervised Machine Learning algorithm used for regression, which is a technique employed to predict continuous outcomes, that consists of fitting a line. It is easily interpretable thanks to its simplicity. Below is a graphical representation of Linear Regression for a single independent variable: Example of a Read more…
Part I: Accuracy and Confusion Matrix There are many different Machine Learning problems, and even within them, there are several ways the objective of the project and the data we have can affect how we assess our model’s performance. We will start with the evaluation metrics used in classification models. Read more…
Ensemble Learning is a method used in Machine Learning that consists of combining multiple models. These models are “base models” or “weak learners”. Weak learners are models that don’t have a good performance, for example, they have high variance or high bias. There are two kinds of ensemble models: Homogeneous: Read more…