Fast Control Gradient Algorithm for Simple and Multiple Linear Regression Model
gradient algorithm, learning rate, linear regression model and mean square error
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Jan Adamowski, Christina Karapataki (2010) Comparison of Multivariate Regression and Artificial Neural Networks for Peak Urban Water-Demand Forecasting: Evaluation of Different ANN Learning Algorithms. 15(10), 729-743.
Samprit Chatterjee, Jeffrey Simonoff (2013) Handbook of Regression Analysis With Applications in R.
Zhihui Chen, Fumin Zou, Lyuchao Liao, Siqi Gao, Meirun Zhang, Jie Chun (2019) Prediction of Electrical Energy Output for Combined Cycle Power Plant with Different Regression Models. 891, 558-566.
Paulo Cortez, António Cerdeira, Fernando Almeida, Telmo Matos, José Reis (2009) Modeling wine preferences by data mining from physicochemical properties. 47(4), 547-553.
Ayşe Demirhan (2018) PERFORMANCE OF MACHINE LEARNING METHODS IN DETERMINING THE AUTISM SPECTRUM DISORDER CASES. 4(1), 79-84.
A Mouatasim, R Ellaia, J Souza De Cursi (2014) Stochastic perturbation of reduced gradient & GRG methods for nonconvex programming problems. 226, 198-211.
A El Mouatasim, M Wakrim (2015) Control Subgradient Algorithm for Image Regularization. 9, 275-283.
A El Mouatasim (2017) Simple and Multi Linear Regression Model of Verbs in Quran. 08(01), 68-77.
A Mouatasim, Y Darmane (2018) Regression analysis of a photovoltaic (PV) system in FPO. 20008.
A El Mouatasim (2019) Control proximal gradient algorithm for image $$ell _1$$ ℓ 1 regularization. 13(6), 1113-1121.
Y Ever, K Dimililer, B Sekeroglu (2019) Comparison of Machine Learning Techniques for Prediction Problems. 927, 713-723.
R Freund, W Wilson, P Sa (2006) Regression analysis: statistical modeling of a response variable.
K Huang, A Hussain, Q Wang, R Zhang (2019) Deep Learning: Fundamentals, Theory and Applications.
J Lakshmi (2016) Stochastic Gradient Descent using Linear Regression with Python. 2(8), 519-524.
Yurii Nesterov (2004) Nonsmooth Convex Optimization. 87, 111-170.
B Shi, S Lyengar (2020) Mathematical Theories of Machine Learning: Theory and Applications.
Aditya Shinde, Purva Raut (2020) Comparative Study of Regression Models and Deep Learning Models for Insurance Cost Prediction. 940, 1102-1111.
Abdullah Smadi, Nour Abu-Afouna (2012) On Least Squares Estimation in a Simple Linear Regression Model with Periodically Correlated Errors: A Cautionary Note. 41(3), 211-226.
J Rawlings, S Pantula, D Dickey (1998) Applied regression analysis: A research tool.
Fadi Thabtah (2017) Machine learning in autistic spectrum disorder behavioral research: A review and ways forward. 44(3), 278-297.
P Tufekci (2014) Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods. 60, 126140.
Yusuf Türkan, Hacer Yumurtacı Aydoğmuş, Hamit Erdal (2016) The prediction of the wind speed at different heights by machine learning methods. 6(2), 179-187.
' Uryas, S (1991) New Variable-Metric Algorithms for Nondifferentiable Optimization Problems. 71(2), 359-388.
L Xinhua, Y Qian (2015) Face Recognition based on Deep Neural Network. 8(10), 29-38.
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2019-11-25
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