#Overview:
The package provides quick train/test split indexing for cross validation, specifically optimized for time series data. There are two primary output options:
- Expanding Window - in which the training window becomes larger with each fold and is always overlapping with part of the previous.
- Rolling Window - in which the training window is of a fixed pre specified dimension, and it may or may not overlap depending on the rolling step specified.
#Example:
''' from time_cross_validation import TimeCV import pandas as pd
#sample X and Y variables: X = pd.DataFrame([10,20,10,4,5,1,7,20]) Y = pd.DataFrame([5,1,7,20,10,20,10,4])
CV = TimeCV(X, train_sample_size = 3, test_sample_size = 3, step = 1) for train_index, test_index in CV.expanding_train_test_split(): x_train = X.iloc[train_index] x_test = X.iloc[test_index] '''
1 maintainer
Metadata
1 maintainer
Release files for time-cross-validation 0.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| time-cross-validation-0.0.2.tar.gz | 1.6 kB | Without provenance | Details for time-cross-validation-0.0.2.tar.gz |
Release files / time-cross-validation-0.0.2.tar.gz
| Download URL | time-cross-validation-0.0.2.tar.gz |
|---|---|
| Size | 1.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f678707f3d9978f92a00eccba5a2348a81f058a43c8d3a2dae542e5d1f694095
|
|
BLAKE2b-256 checksum How to use checksums |
3218179af891db7c6a0370804ce796baf134994f0a985c5b956d9df65fb77bb8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.8
|
Security for time-cross-validation 0.0.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
