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Everything about Hyperparameter (machine learning)
Parameter controlling the machine learning process
In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters or algorithm hyperparameters. These are named hyperparameters in contrast to parameters, which are characteristics that the model learns from the data. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Hyperparameter (machine learning)A 5-minute orientation
- Skim a recent paper: Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive LearningInfluential work since 2022
- Pick up a classic book: Gaussian processes for machine learningThe most-reprinted book on the subject
- Read the landmark paper: On hyperparameter optimization of machine learning algorithms: Theory and practiceCited 3,138 times
- Go sideways: Hyperparameter optimizationA closely related topic
- Go sideways: Federated learningA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
On hyperparameter optimization of machine learning algorithms: Theory and practice
Hyperparameter Search for Machine Learning Algorithms for Optimizing the Computational Complexity
Hyperparameter Tuning for Machine Learning Algorithms Used for Arabic Sentiment Analysis
Hyperparameter Tuning in Machine Learning: A Comprehensive Review
A survey on multi-objective hyperparameter optimization algorithms for machine learning
Multi-Objective Hyperparameter Optimization in Machine Learning—An Overview
Sherpa: Robust hyperparameter optimization for machine learning
Machine learning hyperparameter selection for Contrast Limited Adaptive Histogram Equalization
🆕 Influential since 2022
Machine Learning-Based Boosted Regression Ensemble Combined with Hyperparameter Tuning for Optimal Adaptive Learning
Hyperparameter Optimization in Machine Learning
A review on multi-fidelity hyperparameter optimization in machine learning
Structure Learning and Hyperparameter Optimization Using an Automated Machine Learning (AutoML) Pipeline
Bayesian Hyperparameter Optimization and Ensemble Learning for Machine Learning Models on Software Effort Estimation
📚 Books worth reading
Gaussian processes for machine learningCarl Edward Rasmussen · 2005
Python machine learningSebastian Raschka · 2015- 📕Hyperparameter Tuning with PythonLouis Owen · 2022
- 📕Hyperparameter Tuning for Machine and Deep Learning with REva Bartz, Thomas Bartz-Beielstein · 2022
- 📕Hyperparameter Optimization in Machine LearningTanay Agrawal · 2020
Automated Machine LearningAdnan Masood, Ahmed Sherif · 2021
Neural Networks: Tricks of the TradeGrégoire Montavon · 2012- 📕Hyperparameter Optimization in Machine LearningLuca Franceschi, Michele Donini · 2025
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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