diff --git a/__init__.pyc b/__init__.pyc index 6c0d88a..06cc1d9 100644 Binary files a/__init__.pyc and b/__init__.pyc differ diff --git a/q01_k_means/__init__.pyc b/q01_k_means/__init__.pyc index bff55bc..8a71b7c 100644 Binary files a/q01_k_means/__init__.pyc and b/q01_k_means/__init__.pyc differ diff --git a/q01_k_means/build.py b/q01_k_means/build.py index fca565c..1f8dbbf 100644 --- a/q01_k_means/build.py +++ b/q01_k_means/build.py @@ -10,7 +10,7 @@ y_train = digits.target # Write your solution here : - - - - +def k_means(X_train, y_train, cluster=10, random_state=9): + km=KMeans(init="random", n_clusters=10).fit(X_train) + plt.scatter(y_train, X_train[:,0,0], c=km, s=50) + plt.show() diff --git a/q01_k_means/build.pyc b/q01_k_means/build.pyc index fa56657..227d83b 100644 Binary files a/q01_k_means/build.pyc and b/q01_k_means/build.pyc differ diff --git a/q01_k_means/tests/__init__.pyc b/q01_k_means/tests/__init__.pyc index f6a37b9..f50cb22 100644 Binary files a/q01_k_means/tests/__init__.pyc and b/q01_k_means/tests/__init__.pyc differ diff --git a/q01_k_means/tests/test_q01_k_means.pyc b/q01_k_means/tests/test_q01_k_means.pyc index ac55928..f8bf3c5 100644 Binary files a/q01_k_means/tests/test_q01_k_means.pyc and b/q01_k_means/tests/test_q01_k_means.pyc differ diff --git a/q02_hierarchy_clustering/__init__.pyc b/q02_hierarchy_clustering/__init__.pyc index 9e9464b..e008d0a 100644 Binary files a/q02_hierarchy_clustering/__init__.pyc and b/q02_hierarchy_clustering/__init__.pyc differ diff --git a/q02_hierarchy_clustering/build.py b/q02_hierarchy_clustering/build.py index 2ba8b26..6919f6b 100644 --- a/q02_hierarchy_clustering/build.py +++ b/q02_hierarchy_clustering/build.py @@ -1,12 +1,24 @@ -# Default imports - import pandas as pd import matplotlib.pyplot as plt from sklearn.preprocessing import scale from scipy.cluster import hierarchy from sklearn import datasets - +from scipy.cluster.hierarchy import dendrogram, linkage digits = datasets.load_digits() df = pd.DataFrame(scale(digits.data), index=digits.target) - +df # Write your solution here : +def hierarchy_clustering(X): + Z = linkage(X, 'average') + Z[80] + plt.figure(figsize=(25, 10)) + + plt.title('Hierarchical Clustering Dendrogram') + plt.xlabel('sample index') + plt.ylabel('distance') + dendrogram( + df, + leaf_rotation=90., # rotates the x axis labels + leaf_font_size=8., # font size for the x axis labels + ) + plt.show() diff --git a/q02_hierarchy_clustering/build.pyc b/q02_hierarchy_clustering/build.pyc index 59f6156..37ae4fb 100644 Binary files a/q02_hierarchy_clustering/build.pyc and b/q02_hierarchy_clustering/build.pyc differ diff --git a/q02_hierarchy_clustering/tests/__init__.pyc b/q02_hierarchy_clustering/tests/__init__.pyc index bb41aea..8de4c81 100644 Binary files a/q02_hierarchy_clustering/tests/__init__.pyc and b/q02_hierarchy_clustering/tests/__init__.pyc differ diff --git a/q02_hierarchy_clustering/tests/test_q02_hierarchy_clustering.pyc b/q02_hierarchy_clustering/tests/test_q02_hierarchy_clustering.pyc index d1b4567..f4e631a 100644 Binary files a/q02_hierarchy_clustering/tests/test_q02_hierarchy_clustering.pyc and b/q02_hierarchy_clustering/tests/test_q02_hierarchy_clustering.pyc differ