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Cross-validation
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51	What matters: Size does, Smarts Don’t Albrecht Zimmermann and Bj¨orn Bringmann Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, 3001 Leuven, Belgium {Albrecht.Zimmermann,Bjorn.Brin Add to Reading List Source URL: www.ke.tu-darmstadt.de Language: English - Date: 2009-11-06 11:55:58 Model selection Machine learning Formal sciences Statistical classification Cross-validation Support vector machine Data mining Feature selection DM
52	Using Pre-Trained Models for Fine-Grained Image Classification in Fashion Field Anna Iliukovich-Strakovskaia Alexey Dral Add to Reading List Source URL: kddfashion2016.mybluemix.net Language: English - Date: 2016-08-14 10:56:50 Machine learning Deep learning Convolutional neural network Pattern recognition Artificial neural network Computer vision Boosting Supervised learning Dimensionality reduction ImageNet Statistical classification Cross-validation
53	Dear GEMS users, Discussions with and feedback from GEMS users revealed to us that some users use the system for analysis of extremely small sample datasets. A good heuristic rule for defining extremely small Add to Reading List Source URL: www.gems-system.org Language: English - Date: 2005-10-21 16:55:14 Statistical inference Estimation theory Cross-validation Machine learning Model selection Statistics Estimator Variance Resampling
54	IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1 An Empirical Comparison of Model Validation Techniques for Defect Prediction Models Add to Reading List Source URL: chakkrit.com Language: English - Date: 2016-08-10 02:46:52 Machine learning Computational statistics Statistical inference Regression analysis Model selection Cross-validation Bootstrapping Bootstrap aggregating Logistic regression Overfitting Statistics Autoregressive model
55	Microsoft PowerPoint - cs559f15_Week4.pptx Add to Reading List Source URL: www.cs.stevens.edu Language: English - Date: 2015-09-24 03:35:08 Machine learning Statistical classification Statistics Learning Data Naive Bayes classifier Test set Bayes classifier Cross-validation Glucose
56	An Empirical Study of Just-in-Time Defect Prediction using Cross-Project Models 1 Takafumi Fukushima1 , Yasutaka Kamei1 , Shane McIntosh2 , Add to Reading List Source URL: posl.ait.kyushu-u.ac.jp Language: English - Date: 2014-03-29 02:44:51 Survival analysis Biostatistics Data mining Detection theory Receiver operating characteristic Statistical classification Cross-validation Prediction Ensemble learning Reliability engineering Regression analysis
57	arXiv:1404.0466v2 [cs.LG] 10 JunCholesky Factor Interpolation for Efficient Approximate Cross-Validation Da Kuang Add to Reading List Source URL: arxiv.org Language: English - Date: 2015-06-11 00:22:11
58	KEYWORDS: Rehabilitation, optic nerve, electrical stimulation, artificial neural networks, cross-validation. Add to Reading List Source URL: www0.cs.ucl.ac.uk Language: English - Date: 2011-03-29 16:38:47
59	What You Submit is Who You Are: A Multi-Modal Approach for Deanonymizing Scientific Publications Add to Reading List Source URL: hexhive.github.io Language: English - Date: 2016-06-13 11:08:40 Machine learning Statistical classification Statistics Learning Parts of speech Data Support vector machine Classifier Multi-label classification K-nearest neighbors algorithm Cross-validation