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TaylorFit

TaylorFit is a multivariate polynomial regression application that fits data to a predictive model consisting of a polynomial function, such as

f(x, y) = ax + by + cxy

where x, y, and xy are terms selected by the user, and a, b, and c are coefficients determined using least squares regression.

On the Web

The application works entirely client-side in your browser, so there's no need to download or install anything and no need to create an account. In order to be reasonably efficient, TaylorFit utilizes specific JavaScript primitives and browser capabilities that emulate native execution.

Frameworks used

  • Knockoutjs
  • CoffeeScript

Installation

  1. Ensure npm is installed
    • Run npm --version in terminal to check
    • Install at nodejs.org
  2. Ensure yarn is installed
    • Run yarn --version to check
    • Run npm install yarn to install
  3. Git clone or download a zip of the repo
  4. Open the directory in terminal
  5. Run npm install
  6. Run the server
    • Run npm run debug to start the development server (includes hot reloading)
    • Run npm start to start the production server
  7. Run npm run test to run the test suite

Export to gh-pages

  1. Run npm run build
  2. Copy the build directory
  3. Run git checkout gh-pages
  4. Paste the build directory files into the main directory
  5. Push up the code
  6. Run git checkout master

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Multivariate polynomial regression application that fits data to a predictive model

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  • JavaScript 41.0%
  • HTML 36.7%
  • CoffeeScript 13.1%
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  • Python 1.7%