gpt-gmm-tsne-post.py

import plotly.express as px

# Best model
gmm = GaussianMixture(n_components=7)
gmm.fit(matrix)

# Get aspect labels and give names
labels = gmm.predict(matrix)

aspect_labels = {
    0: "Loans - Repayment, high interest rates, false emails",
    1: "Debt repayment - fraudulent activity, scam",
    2: "Credit Report - false accounts, reporting errors",
    3: "Credit Report - identity theft",
    4: "Privacy - public disclosure of info, consent violation",
    5: "False charges - incorrect account, debt",
    6: "Privacy and identify theft mixed",
    7: "Unknown verification requests"
}

review_data['labels'] = pd.Series(labels).map(aspect_labels)

# Plot
fig = px.scatter(x=x, y=y, color=review_data['labels'], labels=review_data['labels'])
fig.update_layout(
    autosize=False,
    width=1300,
    height=600,
    legend=dict(
        title="Aspect",
        font = dict(size = 10)
    )
)
fig.show()