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Support Vector Machine Kernel Weights
can_yucebas
Member Posts: 7 
Contributor II
Hi to all,
In my analysis I use Support Vecotr Machine (Evolutionary) with Radial Basis Function Kernel. After I finished analysis , I get a result like this:
Total number of Support Vectors: 1124
Bias (offset): -0.011
w[ethni] = -18.791
w[bmi_cat] = -0.728
w[fh_prca] = -79.586
w[pa_cat] = -30.648
w[packyrs_ca] = -108.503
w[ethanol_ca] = 57.925
w[d_lyco_cat] = 24.073
w[p_fat_cat] = 37.213
w[d_calc_cat] = 39.508
w[currsmoke] = -18.024
w[eversmoke] = -8.843
I wonder the meaning of these weights. What they tell me.
Forexample can I interpret the result w[packyrs_ca] = -108.503 as it is the most important attribute (because the weight is highest) that negatively effect the classification result?
In my analysis I use Support Vecotr Machine (Evolutionary) with Radial Basis Function Kernel. After I finished analysis , I get a result like this:
Total number of Support Vectors: 1124
Bias (offset): -0.011
w[ethni] = -18.791
w[bmi_cat] = -0.728
w[fh_prca] = -79.586
w[pa_cat] = -30.648
w[packyrs_ca] = -108.503
w[ethanol_ca] = 57.925
w[d_lyco_cat] = 24.073
w[p_fat_cat] = 37.213
w[d_calc_cat] = 39.508
w[currsmoke] = -18.024
w[eversmoke] = -8.843
I wonder the meaning of these weights. What they tell me.
Forexample can I interpret the result w[packyrs_ca] = -108.503 as it is the most important attribute (because the weight is highest) that negatively effect the classification result?
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