Classic Machine Learning Through the Eyes of an SRE — Part 7 Picture a client health metric that has been flat at 2 out of 10 for six months. Ask PCA to compress your client-health data and that metric will contribute almost nothing to the directions PCA decides to keep. Not because PCA is broken. Because PCA treats variance as importance, and a signal that barely moves contributes almost no variance. Reduce the data far enough and the independent information it carried is simply not ther...