tidied code

app.py

@@ -4,24 +4,6 @@ from sklearn.datasets import make_blobs
 from sklearn.cluster import KMeans
 from sklearn.preprocessing import StandardScaler
 
-# create synthetic data
-features, true_labels = make_blobs(n_samples=200, centers=3, cluster_std=2.75, random_state=42)
-
-# goal:
-#   load in a dataset
-#   take user input for number of clusters
-#   cluster dataset into that many clusters
-
-# page layout:
-#   visualise the data on a plot
-#   normalise the data
-# 
-
-# def greet(name):
-#     return "Hello " + name + "! Welcome to my unsupervised learning space."
-
-# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-
 def compute(number_of_samples, number_of_clusters, randomised_state):
     # create synthetic data
     if randomised_state: seed = None