How can I visualize machine learning results in Python?

How can I visualize machine learning results in Python?

You can use libraries like Matplotlib, Seaborn, and Plotly to create various visualizations for your machine learning results.

Can you give me an example of using Seaborn for visualizing a confusion matrix?

Sure! You can use the heatmap function in Seaborn to visualize a confusion matrix. Here's a simple example:

import seaborn as sns
import matplotlib.pyplot as plt
from sklearn.metrics import confusion_matrix

# Assuming y_true and y_pred are your true and predicted labels
cm = confusion_matrix(y_true, y_pred)

sns.heatmap(cm, annot=True, fmt='d')
plt.xlabel('Predicted')
plt.ylabel('True')
plt.title('Confusion Matrix')
plt.show()

What about visualizing feature importance?

You can visualize feature importance using a bar plot. If you're using a model like Random Forest, you can access the feature_importances_ attribute and plot it using Matplotlib or Seaborn.

Are there any interactive visualization tools I can use?

Yes! You can use Plotly or Bokeh for interactive visualizations. They allow you to create dynamic plots that users can interact with.