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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. day night 87 7 18 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: If mean_grayscale is less than 80 " classify the photo as night else classify the photo as day The PCC for the classification model is 80.0 % The baseline model for this data would be to always classify the photo as night and the baseline model would have a PCC of 72.0 %

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. day night 87 7 18 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: If mean_grayscale is less than 80 " classify the photo as night else classify the photo as day The PCC for the classification model is 80.0 % The baseline model for this data would be to always classify the photo as night and the baseline model would have a PCC of 72.0 %

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 10CYU
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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. day night 87 7 18 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: If mean_grayscale is less than 80 " classify the photo as night else classify the photo as day The PCC for the classification model is 80.0 % The baseline model for this data would be to always classify the photo as night and the baseline model would have a PCC of 72.0 %
Transcribed Image Text: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. day night 87 7 18 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: If mean_grayscale is less than 80 " classify the photo as night else classify the photo as day The PCC for the classification model is 80.0 % The baseline model for this data would be to always classify the photo as night and the baseline model would have a PCC of 72.0 %
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