Machine Learning Model Accuracy by Algorithm

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import ptitprince as pt

np.random.seed(112)
BG_COLOR = '#0a0a0f'
TEXT_COLOR = 'white'
COLORS = ['#5314E6', '#27D3F5', '#F5B027', '#F5276C']

models = ['Random Forest', 'XGBoost', 'Neural Net', 'SVM']
data = pd.DataFrame({
    'Accuracy': np.concatenate([
        np.random.beta(40, 8, 50) * 100,
        np.random.beta(45, 7, 50) * 100,
        np.random.beta(42, 9, 50) * 100,
        np.random.beta(38, 10, 50) * 100
    ]),
    'Model': ['Random Forest']*50 + ['XGBoost']*50 + ['Neural Net']*50 + ['SVM']*50
})

fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

pt.RainCloud(x='Model', y='Accuracy', data=data, palette=COLORS,
             bw=.2, width_viol=.6, ax=ax, orient='h', alpha=.65,
             dodge=True, pointplot=False, move=.2)

ax.set_xlabel('Accuracy (%)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Algorithm', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('ML Model Accuracy Comparison', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#888', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#333')

plt.tight_layout()
plt.show()