Boosting - Learn Data Science with Travis

Clearing air around “Boosting”

Towards Data Science

Boosting is an ensemble meta-algorithm primarily for reducing bias and variance in supervised learning.

The Ultimate Beginner Guide to Boosting

Towards Data Science

Boosting is a meta-algorithm from the ensemble learning paradigm where multiple models (often termed “weak learners”) are trained to solve the same problem and combined to get better results. This…

Boost your grasp on boosting

Towards Data Science

The popularization of boosting has been a major breakthrough in applied machine learning. Inherently easy to implement thanks to multiple software packages while achieving high performance on many…

Boosting Trees and AdaBoost: An Introduction

Analytics Vidhya

Boosting is an iterative assembly mechanism in which models are trained one after the other. These models are referred to as “poor learners” because they are basic prediction rules that only…

Demystifying Maths of Gradient Boosting

Towards Data Science

Boosting is an ensemble learning technique. Conceptually, these techniques involve: 1. learning base learners; 2. using all of the models to come to a final prediction. Ensemble learning techniques…

Understanding gradient boosting from scratch with a small dataset

Towards Data Science

Boosting is a very popular ensemble technique in which we combine many weak learners to transform them into a strong learner. Boosting is a sequential operation in which we build weak learners in…

Types of Boosting Algorithms in Machine Learning

Python in Plain English

Photo by Derrick Mwiti on KDnuggets The combination of several machine learning algorithms is referred to as ensemble learning. Boosting is an ensemble learning technique in machine learning where mul...

Introduction To Gradient Boosting Classification

Analytics Vidhya

Boosting is an ensemble method that combines several weak learners into a strong learner sequentially. In boosting methods, we train the predictors sequentially, each trying to correct its…

Improve Your Boosting Algorithms with Early Stopping

Towards Data Science

Boosting algorithms are largely popular in the data science space, and rightly so. Models that incorporate boosting yield some of the best performances, which is why they are commonplace in both…

Boosting in Machine Learning and the Implementation of XGBoost in Python

Towards Data Science

As an extension of my previous article outlining Ensemble Methods, this blog will dive into Boosting and all it entails. In its simplest form, Boosting is an ensemble strategy thats consecutively…

Gradient Boosting from Theory to Practice (Part 1)

Towards Data Science

Gradient boosting is a widely used machine learning technique that is based on a combination of boosting and gradient descent . Boosting is an ensemble method that combines multiple weak learners (or ...

Strong(er) Gradient Boosting

Towards AI

AI-generated image (craiyon) The idea of boosting in machine learning is based on the question posed by Michael Kearns and Leslie Valiant in 1988/89: “Can a set of weak learners create a single strong...