can anyone write the code for the following algorithm.
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Object list = [1,2,3...n], where
n- number of tuples/records
m- number of attributes
The steps involved in this phase are detailed
Step 1: Construct a dissimilarity matrix ‘d’
using the measurement in definition2.
Step 2. Compute the threshold value, minimum
dissimilarity of each object,
Step 3. Construct a neighbour matrix ‘neigh’.
Step 4. Select the first member of an object list,
form a new cluster with this object as a member.
Group the neighbors of object based on the criteria
given in definition 5. Remove the clustered objects
from the object list.
Step 5. Repeat the above step until the object list
The steps involved in merging of clusters are
Step 1: Select the cluster with least number of
Step 2. The objects in the selected cluster are
relocated based on the Cluster Merging Criteria.
Step 3. The above steps are repeated until no
more merging is possible.
Compute the mode of each column or attribute of
all objects in each cluster. If the number of cluster
produced in Phase II is ‘K1’, then this phase results in
‘K1’ tuples. Consider this as a dataset with “K1”
tuples with ‘m’ attributes and repeat Phase I and