A project to learn about correlation in general, and to test neural networks in web browsers with Brain.js and Tensorflow.js
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The Predictive Power Score (that I will just abbreviate as PPS hereafter) is a statistical metric used to measure the strength of a predictive relationship between two variables. But unlike traditional correlation measures, such as Pearson’s correlation coefficient r, which only work well for linear relationships between two continuous variables, the PPS is designed to handle a wider variety of relationships, including non-linear ones and categorical data.
PPS and its key points, with one first example
The PPS ranges from 0 to 1, where 0 means there’s just no predictive power (the variable is unable to predict the target) and 1 means perfect predictive power (the variable perfectly predicts the target).
Notice that being always equal to or higher than zero, the PPS does not give information about the direction of the relationship as you can get with say Pearson’s correlation coefficient r which spans from -1 for anticorrelation to +1 for full positive correlation. The PPS only measures how well one variable can predict…