Space complexity of classification algorithms

Question

There is a categorical dataset consisting of n instances, m attributes. We are performing categorical clustering into K clusters. What is the space complexity for the following classifiers:

1. Decision Tree classifier

2. Support Vector Machine classifier

3. Artificial neural network with one hidden layer consisting of 2/3rd neurons of input data

4. KNN classifier?

Answer 1

1. Decistion Tree: $\mathcal{O}(1)$ for constant depth (you might have bad accuracy, though)
2. SVM: $\mathcal{O}(K)$ if you use a linear kernel and one-vs-all
3. ANN: I don't know what "2/3rd neurons of input data" means
4. KNN: $\mathcal{O}(n)$ - you have to store all $n$ samples.