𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Flexible constraints for regularization in learning from data

✍ Scribed by Eyke Hüllermeier

Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
210 KB
Volume
19
Category
Article
ISSN
0884-8173

No coin nor oath required. For personal study only.

✦ Synopsis

By its very nature, inductive inference performed by machine learning methods mainly is data driven. Still, the incorporation of background knowledge-if available-can help to make inductive inference more efficient and to improve the quality of induced models. Fuzzy set-based modeling techniques provide a convenient tool for making expert knowledge accessible to computational methods. In this article, we exploit such techniques within the context of the regularization (penalization) framework of inductive learning. The basic idea is to express knowledge about an underlying data-generating process in terms of flexible constraints and to penalize those models violating these constraints. An optimal model is one that achieves an optimal trade-off between fitting the data and satisfying the constraints.

📜 SIMILAR VOLUMES

Learning curve for competency in flexibl
Learning curve for competency in flexible laryngoscopy
✍ Kulsoom Laeeq; Vinciya Pandian; Margret Skinner; Hamid Masood; Charles M. Stewar 📂 Article 📅 2010 🏛 John Wiley and Sons 🌐 English ⚖ 151 KB

## Abstract ## Objectives/Hypothesis: The purpose of our study was to identify the number of attempts required to attain competency in performing flexible laryngoscopy. ## Study Design: Cross‐sectional prospective study. ## Methods: Fifteen medical students were recruited to perform flexible l

Data integration constraints for consist
Data integration constraints for consistent data redundancy in fuzzy databases
✍ Julie Yu-Chih Liu 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 161 KB

Although the problem of data integration in relational databases has been extensively studied, little work has addressed this problem in the context of fuzzy relational databases. Data integration is highly complex in fuzzy relational databases, partially because of the involvement of the resemblanc

Ontogenetic adaptation and learning: A d
Ontogenetic adaptation and learning: A developmental constraint in learning for a thermal reinforcer
✍ Cynthia M. Hoffman; Graham S. Flory; Jeffrey R. Alberts 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 173 KB

demonstrated that 1-, 5-, and 11-day-old rats in a cool environment (25ЊC) acquired an operant head-turning response when rewarded with a 20-s warming of the platform on which they lay. In the current experiment 5-and 11day-old rats in a hot environment (40ЊC) acquired the head-turning response when

Nested effects models for learning signa
Nested effects models for learning signaling networks from perturbation data
✍ Holger Fröhlich; Achim Tresch; Tim Beißbarth 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 465 KB 👁 1 views

## Abstract Targeted gene perturbations have become a major tool to gain insight into complex cellular processes. In combination with the measurement of downstream effects __via__ DNA microarrays, this approach can be used to gain insight into signaling pathways. __Nested Effects Models__ were firs

Bank borrowing constraints and the deman
Bank borrowing constraints and the demand for trade credit: evidence from panel data
✍ Christina V. Atanasova; Nicholas Wilson 📂 Article 📅 2003 🏛 John Wiley and Sons 🌐 English ⚖ 155 KB

## Abstract Monetary policy contractions exacerbate credit constraints stemming from asymmetric information, incentive problems and limited collateral. During such periods financial intermediaries reduce the supply of credit to smaller businesses. Although trade credit is a less desirable alternati

A semi-supervised active learning algori
A semi-supervised active learning algorithm for information extraction from textual data
✍ Tianhao Wu; William M. Pottenger 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 141 KB

## Abstract In this article we present a semi‐supervised active learning algorithm for pattern discovery in information extraction from textual data. The patterns are reduced regular expressions composed of various characteristics of features useful in information extraction. Our major contribution