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Use interpretability to improve and debug your ML model
How I used feature importance to fix my model
Dec 5
•
Christoph Molnar
12
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Use interpretability to improve and debug your ML model
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November 2023
Don't be dogmatic about interpretability-by-design versus post-hoc
When to use which ML interpretation approach
Nov 28
•
Christoph Molnar
11
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Don't be dogmatic about interpretability-by-design versus post-hoc
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But have you considered writing your own evaluation metric?
The Strategic Use of Custom Metrics in Machine Learning
Nov 21
•
Christoph Molnar
15
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But have you considered writing your own evaluation metric?
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Bridging the Gap: From Statistical Distributions to Machine Learning Loss Functions
When I consulted researchers on which statistical analysis to use for their data, a common first step was to think about the distribution of the target…
Nov 14
•
Christoph Molnar
37
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Bridging the Gap: From Statistical Distributions to Machine Learning Loss Functions
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A Grandmaster's Guide to Machine Learning Challenges
Picking the Right Challenges and Succeeding
Nov 7
•
Christoph Molnar
16
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A Grandmaster's Guide to Machine Learning Challenges
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October 2023
Should we stop interpreting ML models because XAI methods are imperfect?
The Case for Imperfect Interpretability
Oct 31
•
Christoph Molnar
9
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Should we stop interpreting ML models because XAI methods are imperfect?
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The Intricate Link Between Compression and Prediction
How Gzip and K-Nearest Neighbors Can Outperform Deep Learning Models
Oct 24
•
Christoph Molnar
21
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The Intricate Link Between Compression and Prediction
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3
Machine learning eats up science
A new era of science without understanding?
Oct 18
•
Christoph Molnar
10
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Machine learning eats up science
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1
What A Horse Can Tell Us About Machine Learning
How to find out whether your model relies on spurious correlations
Oct 10
•
Christoph Molnar
14
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What A Horse Can Tell Us About Machine Learning
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The Case for Uninterpretable Machine Learning
Machine learning excels because it's not interpretable. Not in spite of it. Interpretability is a constraint.Thanks for reading Mindful Modeler…
Oct 3
•
Christoph Molnar
16
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The Case for Uninterpretable Machine Learning
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7
September 2023
Machine learning interpretability from first principles
Understand interpretation methods via functional decomposition
Sep 26
•
Christoph Molnar
16
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Machine learning interpretability from first principles
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Imbalanced data? Why "Do Nothing" should be the default
And when “Do Something” is better.”
Sep 19
•
Christoph Molnar
21
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Imbalanced data? Why "Do Nothing" should be the default
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