Tuning

app.py

@@ -603,7 +603,7 @@ def compute_global_regression(df_combined, embedding_cols, tsne_params, df_f1, r
 
         df_heat = pd.read_csv(f"data/heatmaps_idefics2-patient.csv")
         # feature_options = [col for col in df_heat.columns if col != "name"]
-        feature_options = ["grades", "table_pos", "v_density", "v_info_blocks", "layout", "columns", "table_grid", "header_badge"]
+        feature_options = ["grades", "table_pos", "v_density", "v_info_blocks", "layout", "columns"]
         
         silhouette_vals = []
         for feature in feature_options:
@@ -996,7 +996,7 @@ def run_model(model_name):
         # 2. Proyección de todos los subconjuntos usando los loadings de df_real (para PC completos)
         # Se proyectan real, synthetic y pretrained (si existen) y se agregan todas las PC's.
         df_all = {}
-        # Real
+        # Real OK
         df_real_proj = embeddings["real"].copy()
         # proj_real = reducer_real.named_steps["pca"].transform(df_real_proj[embedding_cols].values)
         proj_real = reducer_real.transform(df_real_proj[embedding_cols].values)