#generalization
Explore Books, Authors and Common Highlights on Generalization
Showing 7 of 7 highlights
A good model is one that generalizes well to unseen data.
From The Hundred-Page Machine Learning Book by Andriy Burkov
The goal of machine learning is to generalize from the training data to unseen data.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Learning is a process of generalization.
From The Master Algorithm by Pedro Domingos
Regularization techniques are essential to prevent overfitting and ensure generalization to new data.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Cross-validation is a technique for assessing how the results of a statistical analysis will generalize to an independent data set.
From The Hundred-Page Machine Learning Book by Andriy Burkov
Overfitting occurs when a model learns the training data too well, including noise and outliers, leading to poor generalization.
From Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
The power of machine learning lies in its ability to generalize.
From The Master Algorithm by Pedro Domingos