Assume you are working in a bank and you have a customer data with 24 columns in which demographic and financial information can be found. However, two columns (e.g. age and birth location) columns have some missing (NAN) values. Which of the following are applicable, if many data points have missing attributes? Select all that is meaningful/applicable. One wrong answer removes one correct answer. Delete attributes with missing values if you think they are also not very relevant Remove the columns even if they have only one missing value 000 Fill the missing values using a random number generator Impute the missing values with the mean value or mode values

Assume you are working in a bank and you have a customer data with 24 columns in which demographic and financial information can be found. However, two columns (e.g. age and birth location) columns have some missing (NAN) values. Which of the following are applicable, if many data points have missing attributes? Select all that is meaningful/applicable. One wrong answer removes one correct answer. Delete attributes with missing values if you think they are also not very relevant Remove the columns even if they have only one missing value 000 Fill the missing values using a random number generator Impute the missing values with the mean value or mode values

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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