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1 changed files with 5 additions and 6 deletions
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@ -5,19 +5,18 @@ from graphs import clustering_plot
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###########################################
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###########################################
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###########################################
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###########################################
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### LIMITES DE LA METHODE KMEANS ###
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### LIMITES DE LA METHODE DBSCAN ###
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### ###
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### ###
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### Données choisies: ###
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### Données choisies: ###
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### cure-t2-4k.arff --> 6 clusters ###
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### aml28.arff --> 5 clusters ###
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### banana.arff --> 2 clusters ###
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### atom.arff --> 2 clusters ###
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### ###
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### ###
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### Etudiant: Abdel Kader CHABI SIKA B. ###
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### Etudiant: Abdel Kader CHABI SIKA B. ###
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### DGEI / 5 SDBD 2020-2021 ###
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### DGEI / 5 SDBD 2020-2021 ###
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###########################################
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###########################################
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###########################################
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###########################################
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# files = ["aml28.arff", "atom.arff"]
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files = ["aml28.arff", "atom.arff"]
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files = ["aml28.arff"]
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n_clusters = {"aml28.arff":5, "atom.arff":2}
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n_clusters = {"aml28.arff":5, "atom.arff":2}
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print("Génération des figures ...")
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print("Génération des figures ...")
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@ -50,4 +49,4 @@ for file in files:
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# Plotting des clusters
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# Plotting des clusters
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clustering_plot([p[0] for p in points], [p[1] for p in points], predictions, xlabel="Abcisses", ylabel="Ordonnes",
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clustering_plot([p[0] for p in points], [p[1] for p in points], predictions, xlabel="Abcisses", ylabel="Ordonnes",
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fig_title="Graphe de visualisation des clusters de "+file+"\nMéthode: DBSCAN",
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fig_title="Graphe de visualisation des clusters de "+file+"\nMéthode: DBSCAN",
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output="DBSCANOutput/limits/bad_clusters_" + file.split(".")[0] + "_eps_and_minsamples_default.png")#, show=True)
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output="DBSCANOutput/limits/bad_clusters_" + file.split(".")[0] + "_eps_and_minsamples_default.png")#, show=True)
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