Dear all,
                I got a code for e1071 package in R for SVM regression. I
have used *m$coefs*  for extracting the coefficients but I am getting only
72 .  How can I extract coefficients of the predictors   set? Does it mean
that I will get only 72  as *Number of Support Vectors:  72. *
**
Thanks in advance

Code:
--------------

library(e1071)
> # create data
> x <- seq(0.1, 5, by = 0.05)
> y <- log(x) + rnorm(x, sd = 0.2)
> # estimate model and predict input values
> m <- svm(x, y)
> new <- predict(m, x)
> m
Call:
svm.default(x = x, y = y)

Parameters:
   SVM-Type:  eps-regression
 SVM-Kernel:  radial
       cost:  1
      gamma:  1
    epsilon:  0.1

*Number of Support Vectors:  72*
*> m$coefs*
> new
           1            2            3            4            5
6            7            8            9           10           11
12
-1.327786564 -1.277059853 -1.221424097 -1.161313628 -1.097200621
-1.029588549 -0.959005127 -0.885994883 -0.811111473 -0.734909901
-0.657938792 -0.580732849
          13           14           15           16           17
18           19           20           21           22
23           24
-0.503805655 -0.427642943 -0.352696474 -0.279378612 -0.208057720
-0.139054438 -0.072638906 -0.009028968  0.051610615  0.109167970
0.163582945  0.214845022
          25           26           27           28           29
30           31           32           33           34
35           36
 0.262990384  0.308098215  0.350286330  0.389706259  0.426537887
0.460983809  0.493263495  0.523607428  0.552251329  0.579430594
0.605375062  0.630304214
          37           38           39           40           41
42           43           44           45           46
47           48
 0.654422894  0.677917633  0.700953619  0.723672382  0.746190188
0.768597174  0.790957190  0.813308346  0.835664193  0.858015504
0.880332573  0.902567958
          49           50           51           52           53
54           55           56           57           58
59           60
 0.924659570  0.946534037  0.968110220  0.989302798  1.010025830
1.030196181  1.049736754  1.068579418  1.086667584  1.103958361
1.120424239  1.136054277
          61           62           63           64           65
66           67           68           69           70
71           72
 1.150854762  1.164849331  1.178078576  1.190599126  1.202482259
1.213812069  1.224683251  1.235198555  1.245465988  1.255595825
1.265697515  1.275876563
          73           74           75           76           77
78           79           80           81           82
83           84
 1.286231447  1.296850678  1.307810045  1.319170135  1.330974176
1.343246256  1.355989966  1.369187496  1.382799201  1.396763660
1.410998202  1.425399923
          85           86           87           88           89
90           91           92           93           94
95           96
 1.439847127  1.454201198  1.468308834  1.482004603  1.495113765
1.507455297  1.518845050  1.529098984  1.538036397  1.545483098
1.551274451  1.555258224
          97           98           99
 1.557297215  1.557271572  1.555080800

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