From acc914a1c3d7ab5eb291d772ea4cd9874b60fee7 Mon Sep 17 00:00:00 2001 From: Abdel-Kader Chabi-Sika-Boni Date: Wed, 11 Nov 2020 14:03:12 +0100 Subject: [PATCH] Uncomment --- part_limits_DBSCAN.py | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/part_limits_DBSCAN.py b/part_limits_DBSCAN.py index a816da4..1fd1309 100644 --- a/part_limits_DBSCAN.py +++ b/part_limits_DBSCAN.py @@ -5,19 +5,18 @@ from graphs import clustering_plot ########################################### ########################################### -### LIMITES DE LA METHODE KMEANS ### +### LIMITES DE LA METHODE DBSCAN ### ### ### ### Données choisies: ### -### cure-t2-4k.arff --> 6 clusters ### -### banana.arff --> 2 clusters ### +### aml28.arff --> 5 clusters ### +### atom.arff --> 2 clusters ### ### ### ### Etudiant: Abdel Kader CHABI SIKA B. ### ### DGEI / 5 SDBD 2020-2021 ### ########################################### ########################################### -# files = ["aml28.arff", "atom.arff"] -files = ["aml28.arff"] +files = ["aml28.arff", "atom.arff"] n_clusters = {"aml28.arff":5, "atom.arff":2} print("Génération des figures ...") @@ -50,4 +49,4 @@ for file in files: # Plotting des clusters clustering_plot([p[0] for p in points], [p[1] for p in points], predictions, xlabel="Abcisses", ylabel="Ordonnes", fig_title="Graphe de visualisation des clusters de "+file+"\nMéthode: DBSCAN", - output="DBSCANOutput/limits/bad_clusters_" + file.split(".")[0] + "_eps_and_minsamples_default.png")#, show=True) \ No newline at end of file + output="DBSCANOutput/limits/bad_clusters_" + file.split(".")[0] + "_eps_and_minsamples_default.png")#, show=True)