Salience and learning rate in concept identification

Incremental Learning of Variable Rate Concept Drift

We have recently introduced an incremental learning algorithm, Learn.NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Learn.NSE is an ensemble of classifiers approach, training a new classifier on each consecutive batch of data that become available, and combining them through an age-adjusted dynamic error based weighted majority voting. ...

Concept maps and meaningful learning in medical education

the relationship between academic self-concept and academic achievement in english and general subjects of the students of high school

according to research, academic self-concept and academic achievement are mutually interdependent. in the present study, the aim was to determine the relationship between the academic self-concept and the academic achievement of students in english as a foreign language and general subjects. the participants were 320 students studying in 4th grade of high school in three cities of noor, nowshah...

a study on rate making and required reserves determination in reinsurance market: a simulation

reinsurance is widely recognized as an important instrument in the capital management of an insurance company as well as its risk management tool. this thesis is intended to determine premium rates for different types of reinsurance policies. also, given the fact that the reinsurance coverage of every company depends upon its reserves, so different types of reserves and the method of their calc...

Measurement of latent cognitive abilities involved in concept identification learning.

INTRODUCTION We used cognitive and psychometric modeling techniques to evaluate the construct validity and measurement precision of latent cognitive abilities measured by a test of concept identification learning: the Penn Conditional Exclusion Test (PCET). METHOD Item response theory parameters were embedded within classic associative- and hypothesis-based Markov learning models and were fit...