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])
