Question 2: a) Build a cluster model to classify diabetes dataset (The one used in our class) after removing the "class" column from your data. You can use the following code to remove the classes from the data: diabetesNew <- diabetes[, 2:4] b) Based on your trials, what is the best number of clusters in this datasets (value of k). c) If the measurement of Glucose, insulin and sspg for a person are 200, 1000, 150 respectively. Create a tibble representing this data, scale it and use the created model to check the cluster of this person

Question 2: a) Build a cluster model to classify diabetes dataset (The one used in our class) after removing the "class" column from your data. You can use the following code to remove the classes from the data: diabetesNew <- diabetes[, 2:4] b) Based on your trials, what is the best number of clusters in this datasets (value of k). c) If the measurement of Glucose, insulin and sspg for a person are 200, 1000, 150 respectively. Create a tibble representing this data, scale it and use the created model to check the cluster of this person

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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