Skip to content

Latest commit

 

History

History
22 lines (13 loc) · 1.12 KB

README.md

File metadata and controls

22 lines (13 loc) · 1.12 KB
Raw

study group matching service

Group matching service using cosine similarity, agglomerative clustering, Multi Dimensional Scaling(MDS).

Used library

  • numpy
  • sklearn (cosine_similarity, AgglomerativeClustering, MDS)
  • json
  • matplotlib

Code

algorithm.py : Main code, here we calculate the cosine similarity, agglomerative clustering, Multi Dimensional Scaling(MDS).

show_clustering.py : Visualize clustered data with matplotlib using Algorithm.py's function

show_matrix.py : Visualize matrix that transforms a cosine similarity based matrix into a distance matrix

students_data.json : Json file of student’s information including vectorized data

vector.py : Preprocessing and vectorize the data from user. Values can be directly entered at the main function and save the data as a json file.