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  • Posted on Thursday December 10, 2020
    Data:Questionnaire data from mall visitors contains sex, age, salary & shopping score (200 rows). Mission:How to predict the cluster group from given age & salary Library used:PandasNumpySeabornMatplotlibScikit Code:import pandas as pdimport numpy as npimport seaborn as snsimport matplotlib.pyplot as pltfrom sklearn.cluster import AgglomerativeClusteringurl = 'https://raw.githubusercontent.com/kokocamp/vlog101/master/vlog101.csv'vlog128 = pd.read_csv(url)vlog128.info()X = vlog128[['Usia','Gaji (juta)']]y = vlog128['Skor Belanja (1-100)']sns.scatterplot(x="Usia",y="Gaji (juta)",data=vlog128,color="red",alpha=0.5)n_clusters = 5X = np.array(X)hc = AgglomerativeClustering(n_clusters, affinity='euclidean', linkage='ward')hc.fit(X)#print(X)nc = []for i in range(n_clusters):  nc.append(i)print(hc.labels_)vlog128["kluster"] = hc.labels_vlog128.head()fig, ax = plt.subplots()sct = ax.scatter(X[:,0],X[:,1], c = vlog128.kluster, marker = "o", alpha = 0.5)plt.title("Hasil Klustering Hierarchical Clustering")plt.xlabel("Usia")plt.ylabel("Gaji (juta)")plt.show()usia = input("Usia (thn): ")usia = int(usia)gaji = input("Gaji (juta): ")gaji = int(gaji)data = [usia,gaji]data = np.array([data])xx = np.append(X,data,axis=0)hasil = hc.fit_predict(xx)print("Prediksi Kluster (0-4): ", hasil[hasil.size-1])fig, ax = plt.subplots()sct = ax.scatter(X[:,0],X[:,1], c = vlog128.kluster, marker = "o", alpha = 0.5)plt.title("Hasil Klustering Hierarchical Clustering")plt.xlabel("Usia")plt.ylabel("Gaji (juta)")plt.scatter(usia,gaji, c = "red", s=100)plt.show()I wrapped the scenario in a Youtube video below. Click this link (http://paparadit.blogspot.com/2020/11/the-algorithms-of-machine-learning.html), if you want to check out for other algorithms. Thank you for for visiting this blog & subs my channel.  Continue Reading »

I LIVE IN JAKARTA

Jakarta is the political, economic and cultural capital of Indonesia. ... Around 230 languages are spoken here and you'll find a wealth of different cultures and communities throughout the capital. ... Jakarta's world-class tourist attractions are renowned across the globe.