RRepoGEO

REPOGEO REPORT · LITE

ModelOriented/DALEX

Default branch master · commit c4791abc · scanned 6/19/2026, 9:16:53 PM

GitHub: 1,473 stars · 169 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
59 /100
Needs work
Category recall
1 / 2
Avg rank #6.0 when recommended
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ModelOriented/DALEX, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Update repository description to explicitly include "interpreting"

    Why:

    CURRENT
    moDel Agnostic Language for Exploration and eXplanation
    COPY-PASTE FIX
    moDel Agnostic Language for Interpreting and Explaining Machine Learning Models
  • mediumreadme#2
    Add a concise problem-solution statement after the H1

    Why:

    COPY-PASTE FIX
    DALEX provides a unified, model-agnostic framework to interpret and explain the predictions and behavior of any complex black-box machine learning model.
  • mediumcomparison#3
    Add a "Comparison with Alternatives" section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison with Alternatives

Unlike tools such as SHAP and LIME which often focus on specific local explanations, DALEX offers a unified, model-agnostic framework for a comprehensive suite of descriptive explanation methods, including PDP, ALE, ICE, breakdown plots, and permutation importance, to provide both local and global insights into any black-box model.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
1 / 2
50% of queries surface ModelOriented/DALEX
Avg rank
#6.0
Lower is better. #1 = top recommendation.
Share of voice
7%
Of all named tools, what % are you?
Top rival
SHAP
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SHAP · recommended 2×
  2. LIME · recommended 2×
  3. ELI5 · recommended 2×
  4. InterpretML · recommended 2×
  5. Yellowbrick · recommended 2×
  • CATEGORY QUERY
    How can I interpret complex black-box machine learning models for better understanding?
    you: not recommended
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. ELI5
    4. InterpretML
    5. Alibi Explain
    6. Yellowbrick
    7. Skater

    AI recommended 7 alternatives but never named ModelOriented/DALEX. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help explain and visualize predictions from any machine learning model?
    you: #6
    AI recommended (in order):
    1. SHAP
    2. LIME
    3. ELI5
    4. InterpretML
    5. Yellowbrick
    6. Dalex ← you
    7. Skater
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of ModelOriented/DALEX?
    pass
    AI named ModelOriented/DALEX explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts ModelOriented/DALEX in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ModelOriented/DALEX explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo ModelOriented/DALEX solve, and who is the primary audience?
    pass
    AI named ModelOriented/DALEX explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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ModelOriented/DALEX — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite