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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… 
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Related topics

Related topics

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AdaBoostB-splineBackpropagationBacktesting

Broader (1)

Machine learning

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Localizing Multiple Objects Using Radio Tomographic Imaging Technology
Low-data-rate wireless networks can be deployed for physical intrusion detection and localization purposes. The intrusion of a… 
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… 
Review
2014
Review
2014
Enhancement of Mahalanobis-Taguchi System via Rough Sets based Feature Selection
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… 
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… 
2008
2008
Ear Detection Based on Improved AdaBoost Algorithm
Ear detection is the most important step of an ear recognition system, and the detection effect of this step directly affects the… 
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… 
Review
2003
Review
2003
An Introduction to Support Vector Machines: A Review
Review of "An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods, Nello Cristianini and John Shawe… 
Highly Cited
2000
Highly Cited
2000
Using artificial intelligence to predict permeability from petrographic data
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