Q$7(30$ points$)$Consider the following dataset comparing apples and oranges based on a few factors. Say we want to classify new fruits as apples or oranges.$(1)[5$ points$]$ Write down the Nave Bayes Classification Formula. What is the Nave Bayes assumption?$(2)[5$ points$]$ Say we want to classify a new fruit with Color $=$ Orange, Taste $=$ Sour, Texture $=$ Hard. With the dataset above, can we ever classify this fruit as an apple? What about an orange? Why or why not?$(3)[10$ points$]$ Using Nave Bayes, compute the prior and the posterior.$(4)[5$ points$]$ What is the label of this fruit?$(5)[5$ points$]$ We were able to calculate probabilities directly, but this is not always the case. Why would we usually use log probabilities instead?