app.py

import gradio as gr
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.datasets import load_breast_cancer
from sklearn.tree import DecisionTreeClassifier

theme = gr.themes.Monochrome(
    primary_hue="indigo",
    secondary_hue="blue",
    neutral_hue="slate",
)

description = f"""
## Description
This demo can be used to evaluate the ability of k-means initializations strategies to make the algorithm convergence robust
"""

with gr.Blocks(theme=theme) as demo:
    gr.Markdown('''
            <div>
            <h1 style='text-align: center'>Empirical evaluation of the impact of k-means initialization 📊</h1>
            </div>
        ''')
    gr.Markdown(description)

demo.launch()