Z-Scores and Data Classification
Summary of my bookmarked Github repositories from Feb 16th, 2017
stat-lms is an npm package that allows you to calculate z-scores using the LMS (lambda-mu-sigma) method. It is particularly useful for skewed distributions where the data does not follow a normal distribution. The package provides functions such as `getZScore` to calculate the z-score for a given value, `getPercentile` to determine the percentile corresponding to a z-score, and `getValueFromZScore` to calculate the value corresponding to a given z-score. It was programmed by TAKAHASHI, Kyohei and is released under the MIT license.
The Z-Score library is a tool that calculates the z-score for numeric object attributes. With a simple installation process (npm install z-score), you can utilize this library to obtain z-scores for your data. By training the library with a set of objects containing attribute values, you can then calculate the z-score for a specific object. The example demonstrates the calculation of the z-score for a temperature of 15 and a pressure of 1122, resulting in a z-score of -2 for temperature and -3 for pressure.