Perform spectral clustering algorithm and validate it with silhouette coefficient

• spectralClusteringFromNeo4j(String node_label, String distance_measure, String graph_type, String parameter, String remove_columns, String laplacian_type, Double number_of_eigenvectors, String number_of_iteration, String distance_measure_kmean)

node_label :

the name of the group of nodes the similarity graph procedure to be perform on

distance_measure :

• "euclidean"
• "manhattan"
• "canberra"
• "cosine"
• "jaccard"
• "bray_curtis"

graph_type :

• "full"
• "eps"
• "knn"
• "mknn"

parameter :

   - sigma value, an Integer, used for fully connected graph calculation (specify inside string "" in neo4j, will be later converted) - integer
   - k nearest neighbor value, an integer used knn, mutual knn graph (specify inside string "" in neo4j, will be later converted) - integer
   - epsilon value, a double, used for epsilon graph calculation - double 

remove_column :

a string of columns to be separated as coma-separated values, eg: "points,class"

laplacian_type :

• "sym"
• "rw"

number_of_eigenvectors:

number of desired eigenvectors and clusters for kmean procedure

number_of_iteration :

the number of optimal iterations (usually 100)

distance_measure_kmean :

• "euclidean"
• "manhattan"
• "cosine"
• "bray_curtis"