ml4t-cpcv SKILL.md skillA
ml4t-cpcv from ml4t/skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add ml4t/skills/ml4t-cpcv@git:20260901.830d7a8Pins git:20260901.830d7a8 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- ml4t/skills
- Path
validation/cpcv/SKILL.md- Versions recorded
- 4
- Latest version
- git:20260901.830d7a8, committed Sep 1, 2026
- First version recorded
- May 28, 2026
- Size
- 4,644 bytes
- Repository stars
- 41
- License
- Apache-2.0
Combinatorial Purged CV generates a distribution of backtest paths instead of a single estimate. Use when quantifying strategy robustness and overfitting probability.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Combinatorial Purged Cross-Validation
Standard k-fold CV on time series produces one biased performance estimate. CPCV generates C(N,k) train/test combinations with purging and embargo, yielding a **distribution** of results that reveals overfitting.
## The Problem
A single train/test split gives one Sharpe ratio - you cannot tell if it is skill or luck. Standard k-fold shuffles temporal order, leaking future information. Even `TimeSeriesSplit` produces only a handful of sequential folds, each with different train sizes, making comparison unreliable. You need many unbiased performance samples to build a distribution.
## The Pattern
Partition data into N groups, select k as test sets, train on the rest. Purge samples whose labels overlap the test boundary, add an embargo buffer. Repeat for all C(N,k) combinations.
### WRONG
```python
from sklearn.model_selection import KFold
# Shuffled k-fold on time series - future leaks into training
cv = KFold(n_splits=5, shuffle=True, random_state=42)
scores = []
for train_idx, test_idx in cv.split(X):
model.fit(X[train_idx], y[train_idx])
scores.append(model.score(X[test_idx], y[test_idx]))
…Read the whole file at its exact version.
How to install
mdr add ml4t/skills/ml4t-cpcv@sha256:df0377fb1b6b5a9bThe line at the top of this page pins the label git:20260901.830d7a8, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_w4slwoyiaznnqeja)
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Versions
The registry has recorded 4 versions of this file, between May 28, 2026 and Sep 1, 2026, about one every 32 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260901.830d7a8 latest | 2026-09-01 | 830d7a8 | 4,644 B | A | view · diff |
| git:20260901.1323bf4 | 2026-09-01 | 1323bf4 | 4,607 B | A | view · diff |
| git:20260901.c415df0 | 2026-09-01 | c415df0 | 4,471 B | A | view · diff |
| git:20260528.303089e | 2026-05-28 | 303089e | 4,531 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (4644 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ml4t/skills · 41 stars · license Apache-2.0 · pushed 2026-11-08 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_w4slwoyiaznnqeja GET https://markdownregistry.com/api/v1/resolve?ref=ml4t/skills/ml4t-cpcv GET https://markdownregistry.com/api/v1/blob/df0377fb1b6b5a9beae2d12293fbab00788ee1e681588b341574e7dbfe71b091
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.