10 docs tagged with "regression"

CatBoost is an efficient gradient boosting algorithm that handles categorical features well, making it a powerful tool for classification and regression problems.

In this post, we'll explore the Decision Tree Algorithm, a popular machine learning model used for classification and regression tasks.

In this post, we’ll explore the Extra Trees Algorithm, an ensemble learning model used for classification and regression tasks, known for its efficiency and randomness in both feature selection and data sampling.

In this post, we'll explore the k-Nearest Neighbors (k-NN) Algorithm, one of the simplest and most intuitive algorithms in machine learning.

In this post, we'll explore the Linear Regression Algorithm, one of the most basic and commonly used algorithms in machine learning.

In this post, we’ll dive into the Random Forest Algorithm, an ensemble learning model used for classification and regression tasks, known for its robustness and versatility.

In this post, we’ll explore the concept of regression in supervised learning, a fundamental approach used for predicting continuous outcomes based on input features.

Definition:

SVM is a powerful machine learning model known for its effectiveness in classification tasks and its ability to handle high-dimensional data.

XGBoost is a highly efficient and scalable machine learning algorithm known for its accuracy and speed in solving both classification and regression problems.