Generate interactive 2x2 confusion matrix visualizations with precision, recall, specificity, accuracy, and F1-scores.
Enter binary classification outcomes (True Positives, False Positives, False Negatives, True Negatives) to generate a visual confusion matrix with accuracy, precision, recall, and F1-score.
Confusion Matrix Visualizer is an online engineering and computational utility designed to provide immediate, high-precision results for students, researchers, and developers.
Calculations use standard precision formulas and client-side processing:
Widely utilized in academic coursework, laboratory experimentation, production engineering, electronic circuit prototyping, and web application development.
Estimate token counts for AI prompts across GPT-4, Claude, Llama 3, DeepSeek, and BPE tokenizers with cost previews.
Analyze AI prompt length, word count, token estimates, section structure, template variables, and instructions.
Calculate MAE, MSE, RMSE, R² score, and MAPE metrics to evaluate regression model performance.
Calculate dataset row allocations and percentage splits for training, validation, and testing sets in ML pipelines.
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