Here is a problem about self-organizing map (SOM).

I want get solutions as detailed as possible so that I could know how you get the answer. Thank you!!!

Question 4 (5+7+8-20 marks) Answer the following questions on competitive learning and Self-Organizing Map (SOM) 1. A cstom has a large amount of docnments on varions different topics (Mythology Sci-fi, Fantasy) and wants to form groups of document belonging to same/similar (depending on how you are extracting features from the documents) topic. How would you solve this problem for the custom (assume the doents are not labeled for you). 5 marks 2. In what situations you would use Kohonen SOMs over K-means clustering? 7 marks] 3. A Kohonen self-organizing map is used to cluster four vectors. Let the vectors to be clustered be (1,1,0,0); (0,0,0,1): (1,0,0,0); (0,0,1,1) The maximum number of clusters to be formed is m 2. Suppose the learning rate is = 0.6, The neighborhood of node J is set so that only one cluster updates its weights at each step (RInitial weight matrix is 0.2 0.8 0.6 0.4 0.5 0.7 0.9 0.3 (a) Calculate the updates in the weight matrix after training the network using the first vector (1, 1, 0, 0) 4 marks] Organizing Map; (3) train the Network; (4) view the Network; (5) plot results (b) Write a Matlab program to (1) load these input vectors; (2) create a Self- using different SOM plots. 4 marks] Question 4 (5+7+8-20 marks) Answer the following questions on competitive learning and Self-Organizing Map (SOM) 1. A cstom has a large amount of docnments on varions different topics (Mythology Sci-fi, Fantasy) and wants to form groups of document belonging to same/similar (depending on how you are extracting features from the documents) topic. How would you solve this problem for the custom (assume the doents are not labeled for you). 5 marks 2. In what situations you would use Kohonen SOMs over K-means clustering? 7 marks] 3. A Kohonen self-organizing map is used to cluster four vectors. Let the vectors to be clustered be (1,1,0,0); (0,0,0,1): (1,0,0,0); (0,0,1,1) The maximum number of clusters to be formed is m 2. Suppose the learning rate is = 0.6, The neighborhood of node J is set so that only one cluster updates its weights at each step (RInitial weight matrix is 0.2 0.8 0.6 0.4 0.5 0.7 0.9 0.3 (a) Calculate the updates in the weight matrix after training the network using the first vector (1, 1, 0, 0) 4 marks] Organizing Map; (3) train the Network; (4) view the Network; (5) plot results (b) Write a Matlab program to (1) load these input vectors; (2) create a Self- using different SOM plots. 4 marks]