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Support vector Training, SVM Train

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rizwan
rizwan on 6 Apr 2015
Commented: rizwan on 6 Apr 2015
Hi Experts,
I want to train SVM for pixel classification as road or non road. Can any one guide me how can i achieve this, What is did for this is given below
clc;
clear all;
load 'D:\MS\Research\Classification Model\Research Implementation\test.mat'; % it loads cp variable having different grey scale values
data = [60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255];
label = ['Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y';'Y'; 'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';'N';];
species = cellstr(label);
groups = ismember(species,'Y');
SVMModel = svmtrain(data,label,'showplot',true,'kernel_function','rbf');
testdata = cp;
testdata2 = reshape(double(testdata),[],1);
classes = svmclassify(SVMModel,testdata2,'Showplot', true);
classes variable is showing N for non road pixel and Y for road pixel, I m not sure if i trained svm correctly using svm train!!!!!!! For road pixel i m assuming grey value range from 59 to 224 and non road pixel range as 1-59 and 225-255, Is it correct??
Please guide

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Answers (1)

michael scheinfeild
michael scheinfeild on 6 Apr 2015
if you have 1 feuters just use histogram and fit to some Gaussian model determine the threshold it seems what you did is correct

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rizwan
rizwan on 6 Apr 2015
Can you write some lines of code how to achieve this?

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