Coding⏱️ 2 min read📅 2026-05-31

How to Fix: ConvergenceWarning: lbfgs failed to converge (status=1): STOP: TOTAL NO. of ITERATIONS REACHED LIMIT

Analyze ConvergenceWarning: lbfgs failed to converge (status=1): STOP: TOTAL NO. of ITERATIONS REACHED LIMIT in scikit-learn.

Quick Answer: The issue is likely due to the KNNImputer not being able to handle categorical data. Try using a different imputer for categorical columns or convert categorical data to numerical values before imputation.

📋 Table of Contents

  1. 💡 Why You Are Getting This Error
  2. 🔧 Proven Troubleshooting Steps
  3. ✨ Wrapping Up

The ConvergenceWarning you're encountering is a common issue when using the L-BFGS algorithm in scikit-learn for optimization tasks. This warning indicates that the L-BFGS solver was unable to converge within the specified maximum number of iterations.

💡 Why You Are Getting This Error

  • [Cause]

🔧 Proven Troubleshooting Steps

Method 1: Adjusting the Optimization Algorithm

  1. Step 1: Change the optimization algorithm from L-BFGS to a more robust one like Broyden-Fletcher-Goldfarb-Shanno (BFGS), Adam, or RMSProp.

Method 2: Increasing the Maximum Number of Iterations

  1. Step 1: Increase the max_iter parameter in your optimizer to a higher value.

✨ Wrapping Up

By implementing one or both of these methods, you should be able to resolve the ConvergenceWarning and successfully train your model.

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