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is it possible if we have different features for different classes of svm?
For example one of the hyperplane:
$$w_1\cdot \text{age}+ w_2 \cdot \text{ trip duration} +w_3 \cdot \text{ income}$$
and the other hyperplane be
$$w_1\cdot \text{cost}+ w_2 \cdot \text{trip duration} +w_3 \cdot \text{purpose of trip}$$
the other one
$$w_1\cdot \text{distance}+ w_2 \cdot \text{trip duration} +w_3 \cdot 0?$$
Does it make sense?
It is possible.
All of these hyperplanes live in the space of
$$\text{(age, trip duration, income, cost, purpose of trip, distace)}$$
even though some of the coefficients are $0$.
Remark: For the last hyperplane $w_3\cdot 0 = 0$.
It is common in multi-class systems to have several different models. These models could conceivably rely on very different feature sets.
One model could rely on features {A,B,C,D} for separating out A from BC. Then another model could be found and tuned with features {D,E,F,G} such that model #2 separates separate B from C.
It is also common to have an "Ensemble" approach to working with multi-class systems, datasets and predictors.
