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Feature Engineering Helper

Listed
jeremylongshore·vlatest·other·MIT

This tool suggests relevant feature engineering techniques to improve your model's performance and accuracy by automating insightful transformations.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill feature-engineering-helper -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

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Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

This skill assists with feature engineering for machine learning models. It can generate new features from existing data, suggest transformations to improve model performance, and help evaluate the impact of different feature sets. The tool aims to streamline the often-laborious process of creating effective features for predictive modeling tasks.

When to use it

  • You're building a machine learning model but struggling with feature selection or creation.
  • You want to improve the accuracy of an existing model by exploring new features.
  • You need help understanding which features are most important for your prediction task.
  • You’re working with complex datasets and require assistance in deriving meaningful insights from raw data.

Key capabilities

  • Feature generation
  • Feature transformation suggestions
  • Feature impact evaluation

Example prompts

  • "Suggest new features based on these columns: age, income, education."
  • "How can I transform the 'date' column to be more useful for my model?"
  • "Evaluate the importance of each feature in this dataset for predicting customer churn."

Tips & gotchas

This skill is most effective when provided with clear information about your data and modeling goals. The quality of suggestions depends heavily on the input data’s structure and content.