How can I visualize anomaly detection results in TensorFlow?
You can use libraries like Matplotlib or Seaborn to visualize the results. Would you like a code example?
Yes, please provide a code example for visualizing anomalies.
Sure! Here's a simple example:
import matplotlib.pyplot as plt
import numpy as np
# Sample data
normal_data = np.random.normal(0, 1, 100)
anomalies = np.random.normal(5, 1, 10)
# Combine data
all_data = np.concatenate([normal_data, anomalies])
# Create a scatter plot
plt.scatter(range(len(all_data)), all_data)
plt.title('Anomaly Detection Visualization')
plt.xlabel('Index')
plt.ylabel('Value')
plt.axhline(y=3, color='r', linestyle='--', label='Anomaly Threshold')
plt.legend()
plt.show()
What does the threshold line represent in the visualization?
The threshold line indicates the value above which data points are considered anomalies. You can adjust it based on your needs.
Can I customize the visualization further?
Absolutely! You can customize colors, markers, and add more features like labels or different styles.
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