iterative-stratification VS timebasedcv

Compare iterative-stratification vs timebasedcv and see what are their differences.

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iterative-stratification timebasedcv
1 1
817 14
- -
0.0 7.1
almost 2 years ago 5 days ago
Python Python
BSD 3-clause "New" or "Revised" License MIT License
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iterative-stratification

Posts with mentions or reviews of iterative-stratification. We have used some of these posts to build our list of alternatives and similar projects.
  • TypeError: unhashable type: 'list' when preparing index of labels for MultiLabelBinarizer
    1 project | /r/CodingHelp | 31 Mar 2021
    I need to create this so I can encode the Labels and run iterative stratification as detailed [here](https://github.com/trent-b/iterative-stratification). Once I have the index prepared, i will run MultiLabelBinarizer to encode the "Labels" list and create a matrix of those values. I will then run the stratification sampling algorithm on that matrix to determine zero-based train and test indices. The code I have below is causing an error.

timebasedcv

Posts with mentions or reviews of timebasedcv. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing iterative-stratification and timebasedcv you can also consider the following projects:

datatap-python - Focus on Algorithm Design, Not on Data Wrangling

tods - TODS: An Automated Time-series Outlier Detection System

auto-sklearn - Automated Machine Learning with scikit-learn

sktime - A unified framework for machine learning with time series

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

aeon - A toolkit for machine learning from time series

Dask - Parallel computing with task scheduling

tslearn - The machine learning toolkit for time series analysis in Python

TSCV - Time Series Cross-Validation -- an extension for scikit-learn

flow-forecast - Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).