Classification Model Confusion Matrix Markdown Table Template
Binary classification confusion matrix comparing actual vs predicted positives and negatives, with precision and recall calculation references.
Interactive Template Customizer
Edit cells, add rows, or sort — changes update the markdown liveColumn Architecture & Alignment Specification
Carefully chosen column alignments ensure optimal visual scannability across desktop and mobile screens:
| Column Header | Alignment | Delimiter Syntax | Design Rationale |
|---|---|---|---|
| Actual \ Predicted | left | :--- | Standard left-aligned readable text & descriptions |
| Predicted Positive | right | ---: | Aligns numeric scale, defaults, or magnitudes |
| Predicted Negative | right | ---: | Aligns numeric scale, defaults, or magnitudes |
| Total Actual | right | ---: | Aligns numeric scale, defaults, or magnitudes |
Pro Tips for Classification Model Confusion Matrix
- Right-align all sample counts.
- Bold True Positives (TP) and True Negatives (TN) for rapid detection of accurate predictions.
- Include row and column totals for clear marginal sum verification.
How to Deploy This Table Across Platforms
Paste raw Markdown into README.md. Leave one blank newline above and below for GFM compliance.
Paste directly into Live Preview mode. Use wikilinks ([[Note]]) inside cells for bidirectional linking.
Press Enter to make a fresh empty line block, then paste. Notion auto-transforms it into a native Simple Table block.
Standard GFM tables work out of the box in modern MDX engines. You can style them via custom CSS selectors.
Raw GFM Code
| Actual \ Predicted | Predicted Positive | Predicted Negative | Total Actual |
| :------------------ | ----------------------: | ------------------------: | ----------------: |
| **Actual Positive** | **850 (True Positive)** | 50 (False Negative) | 900 |
| **Actual Negative** | 30 (False Positive) | **9,020 (True Negative)** | 9,050 |
| **Total Predicted** | 880 | 9,070 | **9,950 (Total)** |Standard padded style with boundary pipes matching GitHub GFM parser specifications.
Platform Support
Syntax Formatting Rules
- Pipe Escaping: Use
\|for text with pipe symbols. - Multi-line Cells: Use
<br>for line breaks. - Monospace Text: Wrap variables or code in backticks (
`key`). - Empty Values: Use
—instead of leaving cells empty.
More Data & AI Markdown Templates
Browse all 50 templatesBig-O Algorithmic Time & Space Complexity
Comprehensive cheat sheet for common data structures and sorting algorithms, comparing best, average, worst time, and space complexity.
Machine Learning Model Benchmark Matrix
Compare machine learning and deep learning models across accuracy, precision, recall, F1 score, model parameter count, and inference latency.
Large Language Model (LLM) Capabilities
Compare frontier foundation models by context window tokens, input token pricing, output token pricing, multimodality, and benchmarks.
Frequently Asked Questions About Classification Model Confusion Matrix
Why are numeric metrics and percentiles aligned to the right in this table?
In data tables, columns containing numbers (such as Predicted Positive, Predicted Negative, Total Actual) are strictly right-aligned using "---:". This aligns decimal places vertically, allowing readers to instantly assess numerical magnitude without mental strain.
Where in my repository or project documentation should I place this Classification Model Confusion Matrix table?
This template is specifically designed for data science notebooks, ml evaluation reports, diagnostic testing analysis. Place it inside your project's README.md, technical wiki, or developer portal. Always leave at least one blank newline before and after the table to ensure the GFM parser detects it properly.
Why is the "Actual \ Predicted" column styled with left alignment?
The "Actual \ Predicted" column functions as the primary key of this table. Setting it to left alignment establishes an anchor along the left reading margin, making it effortless for developers to scan down the list.
How do I add line breaks inside a single cell of this Classification Model Confusion Matrix table?
Standard Markdown table rows cannot contain literal carriage returns. To create a multi-line list inside a cell, insert HTML <br> tags (e.g. "Item 1<br>Item 2<br>Item 3"). This keeps the entire entry in a single clean row without breaking column alignments.
How do I handle optional or missing values in Classification Model Confusion Matrix?
Never leave table cells completely empty, as some strict Markdown parsers may collapse empty pipes. Instead, insert an em-dash ("—"), "N/A", or "None" to explicitly indicate that a value is not applicable.
Can I export this Classification Model Confusion Matrix table into CSV, Excel, or HTML?
Yes. In the interactive toolkit above, you can edit your data and use our integrated export tools to convert this table directly into CSV, JSON, HTML <table>, or LaTeX with a single click.