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Experiment, Learn, Fail, Repeat

Planet Classifier

10/3/2017

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In partnership with Harvard's Center for Astrophysics (CfA), I have begun creating a planet classifier. The plan is to use a deep LRCN network to classify based on light curves. In the past week, I have created a PCA/SVC model to establish a baseline. In theory, the LRCN should do better, but the SVC is already significantly over chance. There were three categories: planet, eclipsing binary (often confused for planets), and junk. The ROC curves and PCA Dimensions vs Accuracy are below. Considering it's a three class problem, a 70% accuracy on validation data is pretty darn good.  : )
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