252,915 Hits in 2.0 sec

Learning curve and interobserver variance in quantification of the optical coherence tomography attenuation coefficient

Ronni Wessels, Daniel M. de Bruin, Dirk J. Faber, Joyce Sanders, Andrew D. Vincent, Marc van Beurden, Ton G. van Leeuwen, Theo J. M. Ruers
2015 Journal of Biomedical Optics  
The learning curve and interobserver variance of attenuation coefficient (μ OCT ) determination from optical coherence tomography (OCT) images were quantified.  ...  The difference between the consensus and student μ OCT values was larger for smaller values of μ OCT .  ...  Acknowledgments The authors would like to thank the students L. van Ginkel, R. Klaassen, and R-J. Goldhoorn for their time and effort in this study.  ... 
doi:10.1117/1.jbo.20.12.121313 pmid:26662606 fatcat:hdwjwerjgrdp5cgcq6tf7cggza

Two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve

Mega Aria Pratama, Cucuk Nur Rosyidi, Eko Pujiyanto
2018 Journal of Industrial Engineering and Management  
Purpose: The aim of this research is to develop a two stages optimization model on make or buy analysis and quality improvement considering learning and forgetting curve.  ...  The inclusions of learning and forgetting also gives a new perspective in quality investment decision.  ...  Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.  ... 
doi:10.3926/jiem.2615 fatcat:g2fy7od5drbjrjq56tphoissre

A unique method for estimating the reliability learning curve of optic nerve sheath diameter ultrasound measurement

Frederick A. Zeiler, Markus T. Ziesmann, Patrick Goeres, Bertram Unger, Jason Park, Dimitrios Karakitsos, Michael Blaivas, Ashley Vergis, Lawrence M. Gillman
2016 Critical Ultrasound Journal  
Ultrasonic measurement of the optic nerve sheath can be quite challenging and there is limited literature surrounding learning curves for this technique.  ...  Conclusions: This study suggests a significant finite learning curve associated with ONSD measurements.  ...  Funding This study was funded by a general operating grant from the Health Science Centre Foundation in Winnipeg, Manitoba, Canada.  ... 
doi:10.1186/s13089-016-0044-x pmid:27501699 pmcid:PMC4977242 fatcat:jydilafjmrgdjh7dr5q5une7py

The Maple 15 Learning Software effect on the conceptual realization, and developing the Afghanistan students' knowledge through curves: A case study in Samangan

Abdul Basir Deljuy
2021 International Journal of Scientific and Research Publications (IJSRP)  
At the beginning of the learning period, a pre-test related to the curves drawing of the tenth class mathematic was taken.  ...  Also, the findings of this study show that learning the algebraic and trigonometric curves drawing by using Maple Software can be effective on the mathematic operation and components' meaningful realization  ...  learning of the curves drawing is not overlooked.  ... 
doi:10.29322/ijsrp.11.09.2021.p11707 fatcat:7ilsed3ltzelrhx75fqvc526uu

The dynamics of time-varying threshold learning

J. Sklansky, N.J. Bershad
1969 Information and Control  
A learning curve is a curve of correct-decision probability versus training length. A variance curve is a curve of the variance of correct-decision probability versus training length.  ...  A mathematical theory of the dynamics of a class of trainable signal detectors is described. Among the constructs yielded by the theory are learning curves and variance curves.  ...  LEARNING CURVES, CENTROID CURVES, AND VARIANCE CURVES The learning curve and the variance curve of a TLP serve as principal means for describing a TLP's dynamic behavior: In the following we show how a  ... 
doi:10.1016/s0019-9958(69)90522-1 fatcat:7liszbglcjdyjh6lwzjrooul4a

Piecewise power laws in individual learning curves

Yoni Donner, Joseph L. Hardy
2015 Psychonomic Bulletin & Review  
The PPL model allows for multiple PLs connected at different points in the learning process. We also explored the transition dynamics between PL curve component pieces.  ...  A piecewise PL (PPL) model explained the individual learning curves significantly better than a single PL, controlling for model complexity.  ...  learning curve that was modeled as a random walk with variance .25.  ... 
doi:10.3758/s13423-015-0811-x pmid:25711183 pmcid:PMC4577530 fatcat:fhutk3p64nfibcx6o3eu7hxee4

Robust principal curves based on maximum correntropy criterion

Chun-Guo Li, Bao-Gang Hu
2013 2013 International Conference on Machine Learning and Cybernetics  
CPC model are insensitive to variances and outliers of data clouds. Extensive experiments on sythetic and real-life datasets illustrate the robustness of CPC model in learning principal curves.  ...  Principal curves are curves which pass throught the 'middle' of a data cloud. They are sensitive to variances of data clouds.  ...  Acknowledgements The authors would like to thank the advice coming from machine learning crew in NLPR.  ... 
doi:10.1109/icmlc.2013.6890365 dblp:conf/icmlc/LiH13 fatcat:ml3yl35h4babdg3q42n7wcfbvi

Getting Your Bias Variance Right and Regularization

Divisha Bera
2018 International Journal of Computer Applications  
A performance metric to judge the model, is to see if it is in the wrong side of bias or variance. While building a classifier, cases with high bias, and high variance crop up.  ...  This paper shall attempt to shed some light on the problem of bias-variance, and how to solve them, with some approaches to perform Regularization.  ...  Fig 1 : 1 Fig 1: Graphical illustration of bias and variance Fig 2 : 2 Fig 2: Learning curve on High Bias Fig 3 : 3 Fig 3: Learning curve on High Variance 4 .Fig 4 : 44 Fig 4: Bias Variance Graphs  ... 
doi:10.5120/ijca2018917579 fatcat:ntp5lzfhjjhd5ld662hmcnzptq

Page 7 of None Vol. 45, Issue 1 [page]

1953 None  
Using variance within groups as error, the F’s show that both learning and similarity are highly significant.  ...  The analysis of variance is sum- marized ir Table 3. It can be seen that learning and similarity do not interact significantly.  ... 

Learning curves for the modeling of sugar cane productivity

Vitor Hiroya Nisieimon, Luiz Henrique Antunes Rodrigues, Felipe Ferreira Bocca, Matheus Ferraciolli
2019 Revista dos Trabalhos de Iniciação Científica da UNICAMP  
In this project, we studied learning curves, a tool used in the analysis of a model's performance according to the amount of data available.  ...  Predicting the final yield of a crop is one of the most important aspects of a mill's agricultural planning. However, numerous factors must be considered to ensure a realistic forecast.  ...  1 . 1 Learning curve for the three techniques used.  ... 
doi:10.20396/revpibic2620181368 fatcat:gjzlwvql2zaxlg72uis25iiocu

Improving operations planning with learning curves: overcoming the pitfalls of 'messy' shop floor data

Timothy L Smunt, Charles A Watts
2003 Journal of Operations Management  
While most of the previous research on learning and experience curves examines cost improvements at the product level, we investigate the use of learning curve analysis at the detailed component part production  ...  However, we also found that by applying simple aggregation methods, we could better determine the accuracy of the predicted learning curve rates.  ...  We also would like to thank Oscar Garza and Alex Wilson for their assistance on the statistical analysis of this data.  ... 
doi:10.1016/s0272-6963(02)00088-8 fatcat:2r4us23krvdgrl3tjizgmnsnam

On the Bias-Variance Tradeoff: Textbooks Need an Update [article]

Brady Neal
2019 arXiv   pre-print
We first review the history of the bias-variance tradeoff, its prevalence in textbooks, and some of the main claims made about the bias-variance tradeoff.  ...  We observe a similar phenomenon beyond supervised learning, with a set of deep reinforcement learning experiments.  ...  startup grant by IVADO and the Canada CIFAR AI chair program.  ... 
arXiv:1912.08286v1 fatcat:amclswbmezdk7iazf2g2bwccd4

Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods

Nir Nissim, Yuval Shahar, Yuval Elovici, George Hripcsak, Robert Moskovitch
2017 Artificial Intelligence in Medicine  
curve of each labeler) and inter-labeler variability (among the learning curves of different labelers).  ...  Finally, using the consensus label led to a learning curve that had a higher mean intra-labeler variance, but resulted eventually in an AUC that was at least as high as the AUC achieved using the gold  ...  Acknowledgments We thank the Malware Lab at the Ben-Gurion University's Cyber Security Research Center (CSRC) and the Medical Informatics Research Center for their support of this research.  ... 
doi:10.1016/j.artmed.2017.03.003 pmid:28456512 pmcid:PMC5937023 fatcat:a25p6bux6ja6tphjrmjpptw4nm

Random walk kernels and learning curves for Gaussian process regression on random graphs [article]

Matthew Urry, Peter Sollich
2013 arXiv   pre-print
We suggest the random walk kernel should be normalised locally, so that each vertex has the same prior variance, and analyse the consequences of this by studying learning curves for Gaussian process regression  ...  Our method for predicting the learning curves using belief propagation is significantly more accurate than previous approximations and should become exact in the limit of large random graphs.  ...  Learning curves for large p Before moving on to the more accurate cavity prediction of the learning curves, we now look at how the learning curves for GP regression on graphs depend on the kernel lengthscale  ... 
arXiv:1211.1328v2 fatcat:4rsoih4kord4jnzh4vx5q2za5m

Learning Curves for Analysis of Deep Networks [article]

Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal M. Shlapentokh-Rothman
2021 arXiv   pre-print
Learning curves model a classifier's test error as a function of the number of training samples.  ...  We propose a method to robustly estimate learning curves, abstract their parameters into error and data-reliance, and evaluate the effectiveness of different parameterizations.  ...  As such, we propose methods to estimate learning curves and their variance from a relatively small number of trained models.  ... 
arXiv:2010.11029v2 fatcat:jhvwn4cmlvbm5c4mo5ctojy6ge
« Previous Showing results 1 — 15 out of 252,915 results