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Poor image recognition performance - suggestions appreciated!
(In case anyone is wondering what I mean by poor performance. I've used cross-validation and my best performance is a precision of 86% [not too bad] and accuracy of 27% [ugh!!]. The model performs much worse than this when applied against other unlabeled images. I also tried using the "similarity" operator (provided by the ImageMiner-1.4.1 extension and it gave me FABULOUS performance on cross-validation (100% precision and 100% accuracy) - but then when I actually used it against more unlabeled images, it failed miserably. It only identified about 30% correctly.)
Thanks in advance.