So I'm working on a supervised text classification problem where I need to classify a 100 classes. The way I look at it, I have following approaches-
100 logistic regression classifications with each class against everything else; and then choose the class with highest logistic regression score
A neural network with n (=3?) Layers with a 100 neurons (1 neuron per class) each. And then use softmax to get 100 probabilities and choose the one with the highest.
Train a Random Forest Classifier? Not sure how good it will be with 100 classes.
Please add any other approaches you think would apply in this case, and let me know what you think will be the best approach here.