import sys
import os
import math
import random
from sklearn import datasets
import numpy as np
# Import helper functions
from mlfromscratch.utils import Plot
from mlfromscratch.unsupervised_learning import DBSCAN
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")
if __name__ == "__main__":
main()
