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Important variable- SVM

1 message · Enoch Gyamfi Ampadu

Original
Enoch Gyamfi Ampadu
# 
Dear List,
Please I need your help.

1. I used the SVM to undertake a forest cover classification. I wanted to
determine the important variable but when I checked the attributes of the
model it does not seem to have that function for that. I wanted to find if
there is a way I could determine it. Find below the attributes for the SVM
model;
$names
 [1] "call"            "type"            "kernel"          "cost"
 "degree"
 [6] "gamma"           "coef0"           "nu"              "epsilon"
  "sparse"
[11] "scaled"          "x.scale"         "y.scale"         "nclasses"
 "levels"
[16] "tot.nSV"         "nSV"             "labels"          "SV"
 "index"
[21] "rho"             "compprob"        "probA"           "probB"
  "sigma"
[26] "coefs"           "na.action"       "fitted"
 "decision.values" "terms"

I also applied the RF for the same image and I am able to determine the
important variable as it has that in the RF attributes. find below the RF
model;

$names
 [1] "call"            "type"            "predicted"       "err.rate"
 "confusion"
 [6] "votes"           "oob.times"       "classes"         "importance"
 "importanceSD"
[11] "local Importance" "proximity"       "ntree"           "mtry"
   "forest"
[16] "y"               "test"            "inbag"           "terms"


2. Please can you also assist me on how to determine the total area covered
by each of the classes. I am not finding my way out on how to determine it
as well.

I will be glad to have your advice.

Thank you.

Best regards,

Enoch