[R] Evaluating statistical models and describing coefficients for non-parametric models

Muhammad Bilal Muhammad2.Bilal at live.uwe.ac.uk
Tue May 17 12:56:56 CEST 2016


Hi All,


I'm using number of models such as lm(), tree, randomForest, svm, and nnet for predicting the delays in projects. Also, I computed the sum of  squared error for all these models for comparison purposes. However, I want to use other related evaluation criteria such as root mean sum of square error (RMSE) and R Squared for evaluation of these models.


My question is that is it possible to compute these criteria (RMSE or R2) for all above-mentioned statistical models.


Second, for the lm() we can see the co-efficient values by checking model summary. Is it possible to see the co-efficient for other models such as SVM and neural network?


Thanks in advance for the help and support.


Many Thanks and


Kind Regards

--
Muhammad Bilal
Research Fellow and Doctoral Researcher,
Bristol Enterprise, Research, and Innovation Centre (BERIC),
University of the West of England (UWE),
Frenchay Campus,
Bristol,
BS16 1QY

muhammad2.bilal at live.uwe.ac.uk<mailto:olugbenga2.akinade at live.uwe.ac.uk>


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