def main():
# Load the dataset
X, y = datasets.make_blobs()
# Cluster the data
clf = GaussianMixtureModel(k=3)
y_pred = clf.predict(X)
p = Plot()
p.plot_in_2d(X, y_pred, title="GMM Clustering")
p.plot_in_2d(X, y, title="Actual Clustering")
def main():
# Load the dataset
X, y = datasets.make_blobs()
# Cluster the data using K-Means
clf = KMeans(k=3)
y_pred = clf.predict(X)
# Project the data onto the 2 primary principal components
p = Plot()
p.plot_in_2d(X, y_pred, title="K-Means Clustering")
p.plot_in_2d(X, y, title="Actual Clustering")
def main():
# Load the dataset
X, y = datasets.make_moons(n_samples=300, noise=0.08, shuffle=False)
# Cluster the data using DBSCAN
clf = DBSCAN(eps=0.17, min_samples=5)
y_pred = clf.predict(X)
# Project the data onto the 2 primary principal components
p = Plot()
p.plot_in_2d(X, y_pred, title="DBSCAN")
p.plot_in_2d(X, y, title="Actual Clustering")
