Edit projet_imt.py

projet_imt.py

@@ -4,15 +4,21 @@ from clustering.agg_clustering import *
 from clustering.mesures_clustering import *
 from results.affichage_messages_par_cluster import *
 from utils.reduction_dimesion import *
+from utils.reduction_dimension_2d import *
+from results.visualize_clusters import *
 
 
 def main():
     # lecture du fichier csv
     df = pd.read_csv("/Users/mac/Desktop/topic_modeling/df_user_messages_new.csv")
     # reduction des dimensions
-    reduced_embeddings = reduce_embeddings(df, n_components=50, random_state=42)
+    reduced_embeddings = reduce_embeddings(df, n_components=100, random_state=42)
+    # rediction des dimension en 2d pour la visualisation
+    reduced_embeddings_2d = reduce_embeddings_2d(reduced_embeddings, n_components=2, random_state=42)
     # clustering
-    labels = agglomerative_clustering(reduced_embeddings, n_clusters=14)
+    cluster_labels = agglomerative_clustering(reduced_embeddings, n_clusters=11)
+    # visualisation des clusters en 2D
+    visualize_clusters(reduced_embeddings_2d, cluster_labels, title="Clusters visualisés en 2D")
     # metriques de clustering
     silhouette_score = compute_silhouette_scores(reduced_embeddings, labels)
     # afficher les resultats