Use following datasetto answerthe following questions: Hungry CashOnHand GoOutToEat L N Y L Y M M Y N H Y Y H Y a. What is the entropy of attribute GoOutToEat orthe entropy of the dataset? b. What is the entropy of Hungry? c. What is the entropy of CashOnHand?

Use following datasetto answerthe following questions: Hungry CashOnHand GoOutToEat L N Y L Y M M Y N H Y Y H Y a. What is the entropy of attribute GoOutToEat orthe entropy of the dataset? b. What is the entropy of Hungry? c. What is the entropy of CashOnHand?

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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Using C. This question deals with processing the semi-annual sales for a drug store. The drug storesells four types of items, namely Cosmetics, Drugs, Stationery, and Confectionery. You havebeen presented with the following set of data which shows sales for the January to June periodfor the various item types. Item Type January February March April May June Cosmetics 8723.19 7397.21 5982.15 8319.54 7298.31 7490.02 Drugs 9384.12 9740.98 8940.34 8876.34 7093.23 9830.11 Stationery 938.25 834.98 976.29 994.56 912.05 849.12 Confectionery 1832.65 972.34 983.65 1289.28 1197.30 989.41 Your job is to develop a program which accepts as inputs the above sales figures and whichdetermines the total sales for the six month period in each category as well as average monthlysales in each category. In addition, your program should also determine the total sales for eachmonth. Your program should produce as output a report with the following format:
The value y (in 1982-1984 dollars) of each dollar paid by consumers in each of the years from 1994 through 2008 in a country is represented by the ordered pairs. (1994, 0.676) (1996, 0.638) (1998, 0.608) (2000, 0.584) (2002, 0.556) (2004, 0.528) (2006, 0.494) (2008, 0.461) (1995, 0.658) (1997, 0.622) (1999, 0.599) (2001, 0.568) (2003, 0.543) (2005, 0.509) (2007, 0.486) (a) Use a spreadsheet software program to generate a scatter plot of the data. Let t = 4 represent 1994. Do the data appear linear? O Yes No (b) Use the regression feature of the spreadsheet software program to find a linear model for the data. (Let t represent time. Round your numerical values to four decimal places.) y 3= (c) Use the model to predict the value (in 1982-1984 dollars) of 1 dollar paid by consumers in 2010 and in 2013. (Round your answers to two decimal places.) 2010 2013 24 Discuss the reliability of your predictions based on your scatter plot and the graph of your linear model for the data. Because the…
Section 2: Consider the whether forecasting dataset shown below: What would be the class of the tuple X (Outlook= Sunny, Humidity: High, Windy: False and Play=Yes)? Show your answer step by step. Outlcok Tenperature Humidity Windy Play Sunny Hot High False No Sunny Hot High True No Overcas Hot High False Yes Rainy Mid High False Yes Rainy Col Normal False Yes Rainy Col Normal True No Overcas Col Normal True Yes Sunny Mid High False No Sunny Cool Normal False Yes Rainy Mid Normal False Yes Sunny Mid Normal True Yes Overcas: Mid High True Yes Overcas Hot Normal False Yes Rainy Mid High True No
Solve in Python, Dataset can be accessed at this link: https://file.io/Gb8ACUwVODtg
You are working as a data scientists and you have received data on house prices in the Boston region. The data set contains the following variables: • crim: per capita crime rate by town • zn: proportion of residential land zoned for lots over 25,000 sq.ft. • indus: proportion of non-retail business acres per town • chas: Charles River dummy variable (= 1 if tract bounds river; 0 otherwise) • nox: nitric oxides concentration • rm: average number of rooms per dwelling •age: proportion of owner-occupied units built prior to 1940 • dis: weighted distances to five Boston employment centers • rad: index of accessibility to radial highways • tax: full-value property-tax rate per $10,000 ptratio: pupil-teacher ratio by town • b: 1000(Bk - 0.63)² where Bk is the proportion of blacks by town Istat: % lower status of the population • medv: Median value of owner-occupied homes in $1000s Given this information: 1. Download the dataset boston.csv and open it as a PANDAS dataframe. 2. Using 'medv'…
Consider a data table, DT, that includes a sample of the population of Turkey. It includes the following variables: id [individual id], fid [family id], province [province name], age, gender, income [monthly income of the person]. How will you find the name of the province where the richest person lives? Oa. DT[income == max(income, na.rm = TRUE] $province b. DT[province, income == max(income, na.rm = TRUE)] c. DT[, list (max(income, na.rm = TRUE)), by = province] d. DT[province, by = max(income, na.rm = TRUE)]
-Give 100 dollars commission to a random employee
Please implement Multinomial Logistic Regression on the following data. Please continue from the given code:
Consider once again the ChickWeight dataset.(comes with base R). Use aggregate to create a new dataframe that gives mean Chick weight at each Time point, for each Diet group. Assign this new dataframe to the variable df . You will only need one line of code: df = ??? If you have done this correctly, you should get the following if you call head(df, 10): head (df, 10) Diet Time weight 0 41.40000 1 1 0 40.70000 0 40.80000 0 41.00000 2 2 3 3 4 4 1 2 47.25000 6 2 2 49.40000 7 3 2 50.40000 4 2 51.80000 1 4 56.47368 10 2 4 59.80000
Butter (g) Milk (ml) Flour (g) Water(ml) Class Su pastry Kol pastry Kol pastry Kol pastry Su pastry Su pastry ???? хо 200 250 200 200 100 300 200 150 100 300 200 хо 50 350 300 275 275 150 175 325 хоо X00 275 225 150 275 400 (Learning outcome 2: will be able to relate Data Mining Models with each other.) 2. (These QUESTIONS are NOT True FALSE questions you have to state and discuss your answer. IF you just write TRUE / FALSE and not describe the REASONS your answer WONT be scored)
Which statement best describes k-means cluster analysis? Question 9 options: It is the process of organizing observations into distinct groups based on a measure of similarity or dissimilarity. It is the process of agglomerating observations into a series of nested groups based on a measure of similarity or dissimilarity. It is the process of reducing the number of variables to consider in data-mining. It is the process of estimating the value of a continuous outcome variable.
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