• FP
  • FN
  • ACC
  • HUMAN

How to analyze classification errors with your AI

Connect your prediction data once. From there, your AI handles the math to find your model's blind spots.

Ask AI about this page

Short answer

How can I find my model's false positives and negatives?

Your AI builds a confusion matrix from your prediction data. This shows you exactly which classes are being misidentified. You'll see the specific counts for every error.

Where errors land.

Error breakdown.

The AI categorizes every misclassification so you can see where the model fails.

FP

False Positive counts

The AI identifies where your model claimed a hit that wasn't there. You get a clear list of these specific errors.

FN

False Negative counts

The AI finds where your model missed a real target. This shows you what your model is currently blind to.

ACC

Accuracy breakdown

The AI calculates the overall correctness across all classes. You see how much of the total data was actually right.

HUMAN

Manual review needed

The AI flags high-confusion pairs. You decide which specific edge cases require a human to re-label the data.

The workflow

What your AI does when prediction data arrives.

The AI takes raw labels and predictions to turn them into error reports.

  1. Data ingestion

    Your AI reads the ground truth and the predicted labels from your provided dataset.

    calculate_confusion_matrix

  2. Matrix generation

    The AI runs the math to map every prediction against the actual outcome.

    calculate_confusion_matrix

  3. Error isolation

    The AI pulls out the specific cells representing false positives and false negatives.

    calculate_confusion_matrix

  4. Pattern detection

    Your AI looks for specific classes that are frequently swapped, helping you find systemic biases.

    calculate_confusion_matrix

Try it

Copy these to start.

Use these prompts to kick off the analysis.

Starting points

Replace the bracketed text with your actual file names or data sources.

Native V8 Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_lcKPfQMdEs9vOL0QvMD7tp5xcmCCFVUKYwiOuwlI/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Native V8 capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "confusion-matrix-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_lcKPfQMdEs9vOL0QvMD7tp5xcmCCFVUKYwiOuwlI/mcp"
    }
  }
}
Copy into chat04

  • Calculate a confusion matrix using the data in my 'predictions_v1.csv' file.

  • Show me the false positives for the 'cat' class in my recent model output.

  • Analyze the confusion matrix from my 'test_results.json' and tell me which classes are most confused.

  • Based on the confusion matrix for my 'image_labels.csv', what are my biggest false negative risks?

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Confusion Matrix Engine once, then ask.

Just link the MCP to your client. Your credentials stay encrypted, and you can start asking questions immediately.

Connect Confusion Matrix Engine to your AI

FAQ

How this task behaves.

  • 01

    Can the AI fix my model's errors?

    No. The AI only identifies and reports the errors. You have to retrain or adjust your model yourself.

  • 02

    Does the AI change my original prediction files?

    No. The AI only reads your data to perform calculations. It never modifies your source files.

  • 03

    Can I use this with any dataset?

    Yes, as long as your data contains clear ground truth labels and predicted labels for the AI to compare.

  • 04

    Will the AI automatically re-label my data?

    No. The AI identifies where the errors are, but it does not perform any data labeling or cleaning.

  • 05

    Can it handle multi-class classification?

    Yes. The tool is designed to handle multiple classes and show how they interact in the matrix.

  • More questions about Confusion Matrix Engine? The Connector page answers them. See everything the Confusion Matrix Engine Connector can do

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