A classification model was developed to predict if a photo of the Tokyo Tower was taken in the day or in the night, based on the mean of the grayscale values. A visual representation of results from testing this model on 25 photos with the tag 'Tokyo Tower' is shown below. Each of the photos were sourced from the website Unsplash and were labelled as actually being taken in the day or the night. 87 7 actual_group day night 18 808 40 80 120 160 mean_grayscale classification incorrect Use the plot above to complete the blanks in the statements below. Be careful to not type any blank spaces, to type the names of the variables and/or levels exactly as they are given in the visualisation or instruction, and to give any percentages rounded to one decimal place (e.g. 25.5% or 32.0%). The decision rule shown above (which may not be a good/sensible one) can be described as: The decision rule shown above (which may not be a good/sensible one) can be described as: If is less than , classify the photo as else classify the photo as The PCC for the classification model is % The baseline model for this data would be to always classify the photo as and the baseline model would have a PCC of %

A classification model was developed to predict if a photo of the Tokyo Tower was taken in the day or in the night, based on the mean of the grayscale values. A visual representation of results from testing this model on 25 photos with the tag 'Tokyo Tower' is shown below. Each of the photos were sourced from the website Unsplash and were labelled as actually being taken in the day or the night. 87 7 actual_group day night 18 808 40 80 120 160 mean_grayscale classification incorrect Use the plot above to complete the blanks in the statements below. Be careful to not type any blank spaces, to type the names of the variables and/or levels exactly as they are given in the visualisation or instruction, and to give any percentages rounded to one decimal place (e.g. 25.5% or 32.0%). The decision rule shown above (which may not be a good/sensible one) can be described as: The decision rule shown above (which may not be a good/sensible one) can be described as: If is less than , classify the photo as else classify the photo as The PCC for the classification model is % The baseline model for this data would be to always classify the photo as and the baseline model would have a PCC of %

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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