PAELLA as a Booster in Weighted Regression

This paper reports the use of the PAELLA algorithm in the context of weighted regression. First, an experiment comparing this new approach versus probabilistic macro sampling is reported, as a natural extension of previous work. Then another different experiment is reported where this approach is tested against a state of the art regression technique. Both experiments provide satisfactory results.

[1]  Joaquín B. Ordieres Meré,et al.  Neural network prediction model for fine particulate matter (PM2.5) on the US-Mexico border in El Paso (Texas) and Ciudad Juárez (Chihuahua) , 2005, Environ. Model. Softw..

[2]  Francisco Ortega,et al.  Importance of information pre‐processing in the improvement of neural network results* , 1996 .

[3]  Yuan-Hai Shao,et al.  An ε-twin support vector machine for regression , 2012, Neural Computing and Applications.

[4]  Beata Walczak,et al.  Neural networks with robust backpropagation learning algorithm , 1996 .

[5]  Joaquín B. Ordieres Meré,et al.  Prediction of daily maximum ozone threshold exceedances by preprocessing and ensemble artificial intelligence techniques , 2016 .

[6]  Ana González-Marcos,et al.  Comparison of models created for the prediction of the mechanical properties of galvanized steel coils , 2010, Journal of Intelligent Manufacturing.

[7]  Joaquín B. Ordieres Meré,et al.  Prediction models for ozone in metropolitan area of Mexico City based on artificial intelligence techniques , 2015, Int. J. Inf. Decis. Sci..

[8]  Manuel Castejón Limas,et al.  Development of neural network-based models to predict mechanical properties of hot dip galvanised steel coils , 2011, Int. J. Data Min. Model. Manag..

[9]  E Salazar-Ruiz,et al.  メキシカリ,バヤカリフォルニア(メキシコ)とカレキシコ,カリフォルニア(アメリカ)における直線と人工知能モデルを用いて対流圏オゾン予測モデルの開発と比較分析 , 2008 .

[10]  Theodore Johnson,et al.  Exploratory Data Mining and Data Cleaning , 2003 .

[11]  J. Ordieres,et al.  Intelligent methods helping the design of a manufacturing system for die extrusion rubbers , 2003, Int. J. Comput. Integr. Manuf..

[12]  Joaquín B. Ordieres Meré,et al.  Development and comparative analysis of tropospheric ozone prediction models using linear and artificial intelligence-based models in Mexicali, Baja California (Mexico) and Calexico, California (US) , 2008, Environ. Model. Softw..

[13]  Manuel Castejón Limas,et al.  Outlier Detection and Data Cleaning in Multivariate Non-Normal Samples: The PAELLA Algorithm , 2004, Data Mining and Knowledge Discovery.

[14]  Héctor Alaiz-Moretón,et al.  Coupling the PAELLA Algorithm to Predictive Models , 2017, SOCO-CISIS-ICEUTE.