Supervised learning - Wikipedia
Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as a human-labeled supervisory signal) train a model.
What Is Supervised Learning? - IBM
Supervised learning, also known as supervised machine learning, is a subcategory of machine learning and artificial intelligence. It is defined by its use of labeled data sets to train algorithms that to classify data or predict outcomes accurately.
Supervised Machine Learning - GeeksforGeeks
Oct 23, 2024 · Supervised machine learning is a fundamental approach for machine learning and artificial intelligence. It involves training a model using labeled data, where each input comes with a corresponding correct output. The process is like a teacher guiding a student—hence the term “supervised” learning.
10 Most Popular Supervised Learning Algorithms In Machine Learning
Mar 17, 2023 · In this guide, you'll learn the basics of supervised learning algorithms, techniques and understand how they are applied to solve real-world problems. We will also explore 10 of the most popular supervised learning algorithms and discuss how …
1. Supervised learning — scikit-learn 1.5.2 documentation
Jan 1, 2010 · 1. Supervised learning. 1.1. Linear Models; 1.2. Linear and Quadratic Discriminant Analysis; 1.3. Kernel ridge regression; 1.4. Support Vector Machines; 1.5. Stochastic Gradient Descent; 1.6. Nearest Neighbors; 1.7. Gaussian Processes; 1.8. Cross decomposition; 1.9. Naive Bayes; 1.10. Decision Trees; 1.11. Ensembles: Gradient boosting, random ...
Supervised machine learning: A brief primer - PMC
This manuscript provides an overview of machine learning with a specific focus on supervised learning (i.e., methods that are designed to predict or classify an outcome of interest). Several common supervised learning methods are described, along with applied examples from the published literature.
Supervised Learning | Machine Learning | Google for Developers
May 14, 2024 · Supervised learning's tasks are well-defined and can be applied to a multitude of scenarios—like identifying spam or predicting precipitation. Foundational supervised learning concepts....
What is Supervised Learning?
Supervised learning is a category of machine learning that uses labeled datasets to train algorithms to predict outcomes and recognize patterns. Unlike unsupervised learning, …
Introduction to Machine Learning: Supervised Learning - Coursera
In this course, you’ll be learning various supervised ML algorithms and prediction tasks applied to different data. You’ll learn when to use which model and why, and how to improve the model performances.
Supervised Machine Learning: A Brief Primer - ScienceDirect
Sep 1, 2020 · Machine learning offers new tools to overcome challenges for which traditional statistical methods are not well-suited. This paper provides an overview of machine learning with a specific focus on supervised learning (i.e., methods that are designed to predict or classify an outcome of interest).
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