Update app.py

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 import numpy as np
 import pandas as pd
 from sklearn.cluster import KMeans, AgglomerativeClustering, DBSCAN, Birch, MeanShift
-from sklearn_extra.cluster import KMedoids
 from sklearn.mixture import GaussianMixture
 from sklearn.decomposition import PCA
 from scipy.cluster.hierarchy import linkage, dendrogram
@@ -23,9 +22,6 @@ def apply_clustering(algorithm, n_clusters, dataset):
     if algorithm == "KMeans":
         model = KMeans(n_clusters=n_clusters, random_state=42)
         labels = model.fit_predict(data_matrix)
-    elif algorithm == "KMedoid (PAM)":
-        model = KMedoids(n_clusters=n_clusters, method='pam', random_state=42)
-        labels = model.fit_predict(data_matrix)
     elif algorithm == "Fuzzy C-Means (FCM)":
         # Use skfuzzy for Fuzzy C-Means
         cntr, u, _, _, _, _, _ = fuzz.cmeans(data_matrix.T, n_clusters, 2, error=0.005, maxiter=1000)
@@ -84,7 +80,6 @@ def main_interface():
     algorithm = gr.Dropdown(
         choices=[
             "KMeans", 
-            "KMedoid (PAM)", 
             "Fuzzy C-Means (FCM)", 
             "Agglomerative Hierarchical Clustering (AHC)", 
             "BIRCH", 
@@ -104,8 +99,11 @@ def main_interface():
         fn=apply_clustering, 
         inputs=[algorithm, n_clusters, dataset], 
         outputs=[output_text, output_image]
-    ).launch(debug=True)
+    ).launch()
 
 # Run the application
 if __name__ == "__main__":
     main_interface()
+
+    
+