Comparison of model selection methods for Boston dataset
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Updated
May 7, 2018 - R
Comparison of model selection methods for Boston dataset
Designing Industrial Experiments, one-way, and two-way ANOVA analysis, Experimental design principles (Replication, Randomization, and Blocking), Parameter Estimation, Sample Variance
Ejercicio de regresiones por distintos métodos (Mejor Selección de Conjuntos, Selección de pasos hacia adelante, Ridge, LASSO, Elastic Net, Componentes Principales, Mínimos Cuadrados Parciales, etc.)
Model Selection Using PCR, PLSR, Best subsets, Ridge Regression and Lasso Regression
Done with Matt Suski as part of the Kaggle Competition
Performing EDA and building model that predicts the selling prices of new homes at a Colorado ski resort
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