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made examples slightly clearer
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@ -143,7 +143,7 @@ int main()
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// print out the number of relevance vectors in the resulting decision function
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cout << "\nnumber of relevance vectors in our learned_function is "
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<< learned_function.function.basis_vectors.nr() << endl;
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<< learned_function.function.basis_vectors.size() << endl;
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// now lets try this decision_function on some samples we haven't seen before
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sample_type sample;
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@ -179,7 +179,7 @@ int main()
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// print out the number of relevance vectors in the resulting decision function.
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// (it should be the same as in the one above)
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cout << "\nnumber of relevance vectors in our learned_pfunct is "
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<< learned_pfunct.function.decision_funct.basis_vectors.nr() << endl;
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<< learned_pfunct.function.decision_funct.basis_vectors.size() << endl;
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sample(0) = 3.123;
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sample(1) = 2;
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@ -144,7 +144,7 @@ int main()
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// print out the number of support vectors in the resulting decision function
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cout << "\nnumber of support vectors in our learned_function is "
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<< learned_function.function.basis_vectors.nr() << endl;
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<< learned_function.function.basis_vectors.size() << endl;
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// now lets try this decision_function on some samples we haven't seen before
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sample_type sample;
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@ -180,7 +180,7 @@ int main()
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// print out the number of support vectors in the resulting decision function.
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// (it should be the same as in the one above)
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cout << "\nnumber of support vectors in our learned_pfunct is "
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<< learned_pfunct.function.decision_funct.basis_vectors.nr() << endl;
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<< learned_pfunct.function.decision_funct.basis_vectors.size() << endl;
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sample(0) = 3.123;
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sample(1) = 2;
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