<--- Back to Details
First PageDocument Content
Statistics / Machine learning / Artificial intelligence / Learning / Statistical inference / Cross-validation / Bootstrapping / Test set / Overfitting / Statistical classification / Pruning / Validation
Date: 2011-11-03 19:34:10
Statistics
Machine learning
Artificial intelligence
Learning
Statistical inference
Cross-validation
Bootstrapping
Test set
Overfitting
Statistical classification
Pruning
Validation

CHAPTER Credibility: Evaluating What’s Been Learned 5

Add to Reading List

Source URL: aml.media.mit.edu

Download Document from Source Website

File Size: 644,17 KB

Share Document on Facebook

Similar Documents

Ethereum / Machine learning / Finance / Economy / Money / Mathematical finance / Blockchains / Cross-platform software / Numerai / Numraire / Overfitting / Data science

Numeraire: A Cryptographic Token for Coordinating Machine Intelligence and Preventing Overfitting Richard Craib, Geo↵rey Bradway, Xander Dunn with Joey Krug https://numer.ai

DocID: 1uXlH - View Document

Is the Cure Worse than the Disease? A Large-Scale Analysis of Overfitting in Automated Program Repair Edward K. Smith Earl T. Barr? Claire Le Goues† Yuriy Brun

DocID: 1utP7 - View Document

Journal of Machine Learning Research1958 Submitted 11/13; Published 6/14 Dropout: A Simple Way to Prevent Neural Networks from Overfitting

DocID: 1ud2W - View Document

Bias-Variance in Machine Learning Bias-Variance: Outline •  Underfitting/overfitting: –  Why are complex hypotheses bad?

DocID: 1tEZn - View Document

Reducing Overfitting in Process Model Induction Will Bridewell Narges Bani Asadi

DocID: 1t6Ho - View Document