Skip to search formSkip to main contentSkip to account menu

Overfitting

Known as: Underfitting, Over-fitted, Overfit 
In statistics and machine learning, one of the most common tasks is to fit a "model" to a set of training data, so as to be able to make reliable… 
Wikipedia (opens in a new tab)

Related topics

Related topics

49 relations
AdaBoostB-splineBackpropagationBacktesting

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
The Role of Data Mining for Business Intelligence in Knowledge Management
This chapter introduces the role of Data Mining (DM) for Business Intelligence (BI) in Knowledge Management (KM), thus explaining… 
2013
2013
Empirical analysis of model selection criteria for genetic programming in modeling of time series system
Genetic programming (GP) and its variants have been extensively applied for modeling of the stock markets. To improve the… 
2013
2013
Combination of activation functions in extreme learning machines for multivariate calibration
Highly Cited
2010
Highly Cited
2010
Shape measurement biases from underfitting and ellipticity gradients
With this study, precision weak gravitational lensing experiments require measurements of galaxy shapes accurate to <1 part in… 
2010
2010
Guidelines for developing effective Estimation of Distribution Algorithms in solving single machine scheduling problems
2009
2009
Semi-supervised learning of semantic classes for query understanding: from the web and for the web
Understanding intents from search queries can improve a user's search experience and boost a site's advertising profits. Query… 
Highly Cited
2005
Highly Cited
2005
Analyzing Behavioral Features for Email Classification
Many researchers have applied statistical analysis techniques to email for classification purposes, such as identifying spam… 
Highly Cited
2000
Highly Cited
2000
Using artificial intelligence to predict permeability from petrographic data
Highly Cited
1997
Highly Cited
1997
Computing Optimized Rectilinear Regions for Association Rules
We address the problem of finding useful regions for two-dimensional association rules and decision trees. In a previous paper we… 
Highly Cited
1986
Highly Cited
1986
Not the Path to Perdition: The Utility of Similarity-Based Learning
A large portion of the research in machine learning has involved a paradigm of comparing many examples and analyzing them in… 
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy (opens in a new tab), Terms of Service (opens in a new tab), and Dataset License (opens in a new tab)