Answered: data set in Table 1, ID refers to…

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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Use decision tree to further explore the dataset, where the dependent variable is ‘smoker’. Please explain the approach taken. [No more than 300 words]
In a 384-well plate luciferase assay, we drugged 4 receptors (A, B, C, D) with their endogenous agonists at a range of doses. Below is a subset of the resulting data frame (please use the full data frame attached to the original email as a CSV file). Each row of this data frame corresponds to a single well of the 384 well plate. The columns are as follows: receptor: the receptor tested in the well agonist: the endogenous agonist used for a receptor agonist_nM: the dose of the endogenous compound (in nanomolar) ● RLU: raw luminescence of the well (our measure of receptor activity) To answer this 3 part question, we’ll ask you to submit a PDF file containing all of your source code, plots, and written interpretation. (Using something like a Jupyter Notebook with Python or Rmarkdown is recommended, but not required.) You should provide brief explanations of your thought process at each step. Part A: Different receptors have different basal rates of activity. To better facilitate…
The following dataset is a historic record of 14 houses that were sold in a small town in BC. The dataset is used to predict whether a new house in the same town will be sold in 10 days if listed with a specific price based on certain attributes. We are considering only four attributes (price, number of bedrooms, size, and distance to bus stop) just to simplify the calculations in this assignment but more attributes should be considered in real applications. Build a decision tree to predict whether a new house listing in the same town will be sold in 10 days based on the given attributes. Use ID3 algorithm. To answer this question, you need to complete the following steps: Calculate the entropy of the whole dataset After identifying the first attribute, repeat the same steps to identify the next attribute to split on in every leaf of the tree based on information gain analysis. Repeat this step until you complete the tree. Draw the final tree

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data set in Table 1, ID refers to identifier for each data point in a 2-D space (i.e., labelled Xi, and Yi). The last colu