ml4t-cpcv skillA
ml4t-cpcv is agent-read markdown (skill) from ml4t/skills: Combinatorial Purged CV generates a distribution of backtest paths instead of a single estimate. Use when quantifying strategy robustness and overfitting probability..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns 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@git:20260901.830d7a8mdr add ml4t/skills/ml4t-cpcv@sha256:df0377fb1b6b5a9bPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_w4slwoyiaznnqeja)
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Versions
| 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 · 19 stars · license Apache-2.0 · pushed 2026-09-24 · 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
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