1 Calculate the distance (dissimilarly) between two data objects with three continuous numeric attributes O1 (5 0, 4 0, 2 0) and O2 (3 0, 5 0, 0 0) Show calculations and final results Manhattan distance (O1, O2) Euclidean distance (O1, O2) in weka What is the purpose of splitting the data set into a training data set and a test data set Why some people split the data into training and testing 1 The following model is used by a books are us data warehouse Time (Time id, Month, Year) Customer Demographics (Dem id, Age group, Min age, Max age, Gender) Facts (Time id, Dem id, Total Sales Amount, No of books sold) Write an SQL query to list the total books purchased by female customers (Gender F) in December 2015

Question

1  Calculate the distance (dissimilarly) between two data objects with three continuous numeric attributes  O1 (5 0, 4 0, 2 0) and O2 (3 0, 5 0, 0 0)  Show calculations and final results  Manhattan distance (O1, O2)   Euclidean distance (O1, O2)   in weka What is the purpose of splitting the data set into a training data set and a test data set Why some people split the data into training and testing  1  The following model is used by a books are us data warehouse  Time (Time id, Month, Year) Customer Demographics (Dem id, Age group, Min age, Max age, Gender) Facts (Time id, Dem id, Total Sales Amount, No of books sold) Write an SQL query to list the total books purchased by female customers (Gender   F) in December 2015

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1. Calculate the distance (dissimilarly) between two data objects with three continuous numeric attributes: O1 (5.0, 4.0, 2.0) and O2 (3.0, 5.0, 0.0). Show calculations

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