Dataset Splitter

Name: Dataset Splitter
Author: jeremylongshore

byjeremylongshore

•

706

数据科学与机器学习

Automates the partitioning of data into training, validation, and testing sets for machine learning model development.

关于

Streamline machine learning workflows by automating the essential step of dividing raw datasets into functional subsets. This skill analyzes user-specified ratios and file locations to generate and execute Python code that creates robust training, validation, and testing partitions. By incorporating best practices such as randomization and data integrity verification, it ensures that your data is properly prepared for unbiased model evaluation and training, allowing developers to move from raw data to model training faster.

主要功能

Automated generation of Python scripts for data partitioning
Configurable ratios for training, validation, and testing sets
Implementation of randomization to ensure unbiased subsets
Data integrity verification to prevent loss or corruption during splitting
Support for stratification to maintain class distributions in imbalanced data
706 GitHub stars

使用场景

Preparing raw CSV datasets for supervised machine learning model training
Creating validation sets to tune model hyperparameters and prevent overfitting
Partitioning large datasets into train-test splits for model performance evaluation

关于

主要功能

Automated generation of Python scripts for data partitioning
Configurable ratios for training, validation, and testing sets
Implementation of randomization to ensure unbiased subsets
Data integrity verification to prevent loss or corruption during splitting
Support for stratification to maintain class distributions in imbalanced data
706 GitHub stars

使用场景

Preparing raw CSV datasets for supervised machine learning model training
Creating validation sets to tune model hyperparameters and prevent overfitting
Partitioning large datasets into train-test splits for model performance evaluation