[R] Evaluating statistical models and describing coefficients for non-parametric models
Muhammad2.Bilal at live.uwe.ac.uk
Tue May 17 12:56:56 CEST 2016
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
Research Fellow and Doctoral Researcher,
Bristol Enterprise, Research, and Innovation Centre (BERIC),
University of the West of England (UWE),
muhammad2.bilal at live.uwe.ac.uk<mailto:olugbenga2.akinade at live.uwe.ac.uk>
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