42 lines
910 B
Python
42 lines
910 B
Python
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
from mpl_toolkits.mplot3d import Axes3D
|
|
from sklearn.cluster import KMeans
|
|
from sklearn.datasets import make_blobs
|
|
|
|
# Generate Question 1 Data
|
|
X, y = make_blobs(n_samples=500, n_features=3, centers=4, random_state=5)
|
|
|
|
|
|
def plot_q1_data():
|
|
fig = plt.figure()
|
|
ax = Axes3D(fig)
|
|
ax.scatter(X[:, 0], X[:, 1], X[:, 2]);
|
|
|
|
|
|
# Generate Question 2 Data
|
|
Z, y = make_blobs(n_samples=500, n_features=5, centers=2, random_state=42)
|
|
|
|
|
|
def plot_q2_data():
|
|
fig = plt.figure()
|
|
plt.scatter(Z[:, 0], Z[:, 1]);
|
|
|
|
|
|
# Generate Question 3 Data
|
|
T, y = make_blobs(n_samples=500, n_features=5, centers=8, random_state=5)
|
|
|
|
|
|
def plot_q3_data():
|
|
fig = plt.figure()
|
|
ax = Axes3D(fig)
|
|
ax.scatter(T[:, 1], T[:, 3], T[:, 4]);
|
|
|
|
# Plot data for Question 4
|
|
|
|
|
|
def plot_q4_data():
|
|
fig = plt.figure()
|
|
ax = Axes3D(fig)
|
|
ax.scatter(T[:, 1], T[:, 2], T[:, 3]);
|