100 days of machine learning (37): 037 Naive Bayes - pick a good watermelon!

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100 days of machine learning, today's talk is: Naive Bayes - pick a good watermelon!

Red Stone has already understood Bayesian theorem and Naive Bayesian method, and can now buy melons with confidence. Before buying melons, there is one more thing to do, which is to collect sample data. Red Stone obtained a set of data containing 10 groups of samples through online information and consultation. This set of data is whether the watermelons corresponding to different melon pedicles, shapes, and colors are raw or cooked. I regard this set of data as historical experience data and use it as a standard.

Among them, feature $X$ is divided into three:melon pedicle, shape, color, melon pedicle is divided intopeeledandnot peeled off, shape is divided intoroundand