Machine Learning, Principal Component, Artificial Intelligence, Unsupervised Learning, Pca Analysis.
means we want to describe the data with fewer features. In doing so, we accept that we will capture less than 100% of the variance. We are essentially trading off some of the explained variance for a simpler, lower-dimensional representation of the dataset. This trade-off can be beneficial,