def main(): numexe = 100 numclusters = 3 viz = Visualizer() clustering = Clustering() appList = AppList() appList.get_data("AppStore/AppleStore.csv", numexe + 1) titles = [ "Clusters after PCA (2D), kmeans, without normalization, clusters #: " + str(numclusters), "Clusters after PCA (3D), kmeans, without normalization, clusters #: " + str(numclusters), "Clusters after PCA (2D), AHC, without normalization, clusters #: " + str(numclusters), "Clusters after PCA (3D), AHC, without normalization, clusters #: " + str(numclusters), "Clusters before PCA (2D), kmeans, without normalization, clusters #: " + str(numclusters), "Clusters before PCA (2D), AHC, without normalization, clusters #: " + str(numclusters), "Clusters after PCA (2D), kmeans, with normalization, clusters #: " + str(numclusters), "Clusters after PCA (3D), kmeans, with normalization, clusters #: " + str(numclusters), "Clusters after PCA (2D), AHC, with normalization, clusters #: " + str(numclusters), "Clusters after PCA (3D), AHC, with normalization, clusters #: " + str(numclusters), "Clusters before PCA (2D), kmeans, with normalization, clusters #: " + str(numclusters), "Clusters before PCA (2D), AHC, with normalization, clusters #: " + str(numclusters) ] arr = np.asarray(appList.retrieve_table(False)) viz.reduce_dim(2, numexe, arr[1:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[0]) viz.reduce_dim(3, numexe, arr[1:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[1]) viz.reduce_dim( 2, numexe, arr[1:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[2] + ", Dendrogram"), titles[2]) viz.reduce_dim( 3, numexe, arr[1:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[3] + ", Dendrogram"), titles[3]) viz.visualize(2, numexe, arr[2:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[4]) viz.visualize( 2, numexe, arr[2:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[5] + ", Dendrogram"), titles[5]) arr = np.asarray(appList.retrieve_table(True)) viz.reduce_dim(2, numexe, arr[1:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[6]) viz.reduce_dim(3, numexe, arr[1:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[7]) viz.reduce_dim( 2, numexe, arr[1:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[8] + ", Dendrogram"), titles[8]) viz.reduce_dim( 3, numexe, arr[1:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[9] + ", Dendrogram"), titles[9]) viz.visualize(2, numexe, arr[2:], clustering.kmeans_fit(numclusters, (arr[1:]).T), titles[10]) viz.visualize( 2, numexe, arr[2:], clustering.ahc_fit(numclusters, (arr[1:]).T, titles[11] + ", Dendrogram"), titles[11])