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Overfitting
Results: 129

#	Item
51	Common Mistakes in Building QSAR Models Damjan Krstajić Research Centre for Cheminformatics Belgrade, Serbia www.rcc.org.rs Add to Reading List Source URL: cisrg.shef.ac.uk Language: English - Date: 2014-03-31 11:07:35 Model selection Estimation theory Econometrics Cross-validation Quantitative structure–activity relationship Linear regression Feature selection Tikhonov regularization Overfitting Statistics Machine learning Regression analysis
52	A Machine Learning Approach for Stock Price Prediction ∗ Carson Kai-Sang Leung Richard Kyle MacKinnon Add to Reading List Source URL: www.cs.umanitoba.ca Language: English - Date: 2014-08-12 21:37:58 Formal sciences Regression analysis Support vector machine Data mining Overfitting Tree decomposition Statistics Machine learning Statistical classification
53	Hydrology and Earth System Sciences, 9(4), 313321Simulationof©flood EGU flow in a river system using ar tificial neural networks Simulation of flood flow in a river system using artificial neural Add to Reading List Source URL: www.hydrol-earth-syst-sci.net Language: English - Date: 2014-12-04 01:58:47 Learning Artificial neural network Activation function Multilayer perceptron Backpropagation Perceptron Early stopping Overfitting Training set Neural networks Statistics Cybernetics
54	Appears in From Statistics to Neural Networks: Theory and Pattern Recognition Applications, V. Cherkassky, J.H. Friedman and H. Wechsler (eds.), NATO ASI Series F, Springer-VerlagPrediction Risk and Architecture Add to Reading List Source URL: www.smartquant.com Language: English - Date: 2014-02-08 06:27:50 Regression analysis Model selection Least squares Cross-validation Resampling Pruning Overfitting Training set Estimation theory Statistics Machine learning Statistical inference
55	A study of the NIPS feature selection challenge Nicholas Johnson November 29, 2009 Abstract The 2003 Nips Feature extraction challenge was dominated by Bayesian approaches developed by the team of Radford Neal and Jiangu Add to Reading List Source URL: statweb.stanford.edu Language: English - Date: 2009-12-14 18:18:01 Ensemble learning Neural networks Regression analysis Computational neuroscience Early stopping Boosting Overfitting Statistical classification Logistic regression Machine learning Statistics Learning
56	8.6 Bayesian neural networks (BNN) [Book, Sect[removed]While cross-validation allows one to find the weight penalty parameters which would give the model good generalization capability, the separation of the data record in Add to Reading List Source URL: www.ocgy.ubc.ca Language: English - Date: 2013-11-09 02:48:24 Machine learning Computational science Econometrics Cross-validation Resampling Bootstrapping Bootstrap aggregating Numerical weather prediction Overfitting Statistics Statistical inference Computational statistics
57	Improving Decision Tree Pruning through Automatic Programming Stig-Erland Hansen Roland Olsson Add to Reading List Source URL: www.nik.no Language: English - Date: 2007-10-16 02:55:08 Computational statistics Ensemble learning Pruning Decision tree learning Overfitting Boosting Ross Quinlan AdaBoost Algorithm Machine learning Decision trees Artificial intelligence
58	Important points to remember Machine learning is the systematic study of algorithms and systems that improve their knowledge or performance with experience. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Add to Reading List Source URL: www.cs.bris.ac.uk Language: English - Date: 2012-04-23 06:41:00 Linear classifier Receiver operating characteristic Margin classifier Calibration Overfitting Supervised learning Book:Machine Learning - The Complete Guide Statistics Statistical classification Naive Bayes classifier
59	A Primer on Predictive Models Add to Reading List Source URL: www.nature.com Language: English - Date: 2014-01-08 13:05:08 Data analysis Business intelligence Data mining ADAPA Receiver operating characteristic Training set Overfitting Economic model Logistic regression Statistics Regression analysis Machine learning
60	Implementation of a Neural Network for Retrieving Atmospheric Parameters from Remote Sensing Philippe BARON, Jana MENDROK, and KASAI Yasuko A numerical model of a supervised feedforward Neural Network (NN) has been imple Add to Reading List Source URL: www.nict.go.jp Language: English - Date: 2013-11-21 20:06:19 Artificial intelligence Multilayer perceptron Feedforward neural network Perceptron Activation function Overfitting Principal component analysis Supervised learning Early stopping Neural networks Statistics Cybernetics