Information Technology > Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 10 Complete Solutions - Introduction To Analytics (All)
ISYE6501 HOMEWORK 10 Question 14.1 The breast cancer data set breast-cancer-wisconsin.data.txt from http://archive.ics.uci.edu/ml/ machine-learning-databases/breast-cancer-wisconsin/ (description a... t http://archive.ics.uci.edu/ml/ datasets/Breast+Cancer+Wisconsin+%28Original%29 ) has missing values. 1. Use the mean/mode imputation method to impute values for the missing data. 2. Use regression to impute values for the missing data. 3. Use regression with perturbation to impute values for the missing data. 4. (Optional) Compare the results and quality of classification models (e.g., SVM, KNN) build using (1) the data sets from questions 1,2,3; (2) the data that remains after data points with missing values are removed; and (3) the data set when a binary variable is introduced to indicate missing values. Question 15.1 Describe a situation or problem from your job, everyday life, current events, etc., for which optimization would be appropriate. What data would you need? I worked at a bank, and our fraud agents needs to review Direct Deposits that we identified as suspiscious. In that case, I built a logistic regression model to identify the Deposits that are more likely to be suspiscious. The challenge is that we can only use model score to prioritize the queue. Also Deposit with higher amounts might have a higher priority. Moreover, Deposits are processed in batch at different time of the day, so depending on the time of the day, the day of the week and the week of the monther, the quantity of deposits might differ; and agents have a limited time to review the suspicious deposits. So since agents are a limited resource, optimization might be appropriate to estimate the number of agent needed at any given time of the day. The data that I would need is: * The list of deposits at any given time/day, the amount and the fraud score. * The team budget, the max number of agents on week days vs week ends, and the average time spent to review each. * The minimum penetration rate(reviewed deposits over total deposit) [Show More]
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 10 Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 14.1 The breast cancer data set breast-cancer-wisconsin.data.txt from http://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/ (description at http://archive.ics.u...
By Tessa , Uploaded: May 16, 2022
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 8 Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 11.1 I load the uscrime.txt file into R I notice that this model includes all the factors except for Pop. Comparing the quality of fit of all three models, I would use the stepwise regress...
By Tessa , Uploaded: May 16, 2022
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 10 Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 14.1 The breast cancer data set breast-cancer-wisconsin.data.txt. 1. Use the mean/mode imputation method to impute values for the missing data. 2. Use regression to impute values for the m...
By Tessa , Uploaded: May 16, 2022
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 8 - STEPWISE REGRESSION, LASSO AND ELASTIC NET- Complete Solution - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Abstract Use different Regression models to look at the crime data with scaling to align and assess alpha across stepwise, lasso, and elastic net regressions.
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 12 Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 18.1 Describe analytics models and data that could be used to make good recommendations to the power company. Here are some questions to consider: • The bottom-line question is which shutof...
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Introduction To Analytics Modeling - GTX ISYE 6501 Homework 2 Solutions (All)
Georgia Institute Of Technology ISYE 6501 Introduction To Analytics Modeling - GTX ISYE 6501 Homework 2 Solutions
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 13 - Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 18.1 Describe analytics models and data that could be used to make good recommendations to the power company. Here are some questions to consider: •The bottom-line question is which shutof...
By Tessa , Uploaded: May 16, 2022
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Information Technology> Solutions Guide > City University of Hong Kong - IS 3430IS3430_Tutorial_WK8_Solution. (All)
IS3430 Systems Analysis and Design ______________________________________________________________________________ City University of Hong Kong ▪ Department of Information Systems 1/2 Tutorial Week...
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 12 : Power Company Case - Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
ISYE 6501 Homework 12: Power Company Case In approaching the power company case study, I find it best to break the problem into three more discrete and manageable parts. For each of these parts we c...
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Information Technology> Solutions Guide > Georgia Institute Of Technology ISYE 6501 Homework 14 - Complete Solutions - Introduction To Analytics Modeling - GTX ISYE 6501 (All)
Question 19.1 Describe analytics models and data that could be used to make good recommendations to the retailer. How much shelf space should the company have, to maximize their sales or their profi...
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