Cross-validated accuracy of classification in cat/dog recognition. Panel (a) compares using r learned sensors/features (solid red and green lines) against using r random pixel sensors (dashed blue line) and projections onto the first r principal components of the full image (solid blue line). Each data point summarizes 400 random iterations. At each iteration, a different 90% subsample was used to train the classifier, whose accuracy was assessed on the remaining 10% of images. Error bars are standard deviations. (b) A summary of meancross-validated accuracy varying p, the number of pixels used in the random subsample, and r, the number of features/sensors used to construct the classifier.