can u solve this?

After collecting a large number of observable characteristics, X, on a sample of individuals as well as their membership in one of two possible classes - Y=0 or Y=1 - an analyst performs a principal component analysis (PCA) of the data on X. Results up to the six-th principal component is reported in the following table. Principal Proportion Cumulative Component explained 0.6621 0.6621 0.2425 0.9046 3 0.0282 0,9328 4 0.0174 0.9502 0.0099 0.9601 0.0051 0.9652 8) The picture here below represents the scatterplot of the second principal component (PC2) versus the first one (PC1). Each dot represents a sample unit, the color of the dot represents its label Y. Given the results of PCA, the analyst claims that to solve the problem of predicting Y one can use this picture instead of using the whole set of characteristics X. Is the analyst right? Explain. Y=0 Y=1 PC2 -3 -2 -1 PCI