I am trying classify an input graph (a 2D point sequence) into one of the predefined graphs (A,B,C etc) using machine learning. The goal is to identify which type of graph the input graph belongs to.
I have done classification of single data points before, but I have never classified sequences of data like graphs before. The only way I could think of is calculating 'mean squared error' between input & each of A,B,C graphs and choose the category with the lowest error.
3 example outputs might look like this.
input graph belongs to type A (confidence: 82%) input graph belongs to type C (confidence: 68%) input graph doesn't belong to any type (max confidence: 12%)
How can I achieve this using classification techniques or any other accurate way?