labels.append(2)
else:
labels.append(3)
elif preset == "Wings":
for index in range(len(kX)):
if index in dataBase.goalkeepers:
labels.append(0)
else:
if index in dataBase.wings:
labels.append(1)
else:
labels.append(2)
# Plot the results
kmeans.plot(labels, pred, kX)
# Clustering with Bisecting KMeans
bkmeans = BisectingKMeans()
bkmeans.setK(clusters)
bkmeans.setNrIterations(10)
bkmeans.fit(bkX)
pred = bkmeans.predict(bkX)
# Make plot for KMeans
# Convert data points to 2D points for plotting
pca = PCA(n_components=2)
bkX = pca.fit_transform(bkX)
# Make labels based on player position
from create_cluster_data import create_cluster_data import maths as mth from KMeans import KMeans from sklearn.preprocessing import scale data = create_cluster_data(1000, 5) kmean = KMeans(mth.standardize(data)) kmean.fit() kmean.iterate() kmean.plot()
