The current report is a summary of various techniques that are used to for recommendation. The inspiration behind the Image Classification problem considered for this project is employing deep learning techniques and TensorFlow like advanced data processing libraries hosted in Python to classify data. The response rate is 16.88%, 10.57%, 6.92%, 2.30%, and 5.85% for strata 1 to 5, respectively. The BG/NBD model was first introduced by Fader, Hardie and Lee in 2004 for predicting expected future transactions and survival probability for customers in a non-contractual setup. Cincinnati Bell, like many telecommunication companies, faces the problem of customer churn. Mayur Bhat, Study of Uplift Modeling and Logistic Regression to increase ROI of Marketing Campaigns, June 5, 2009 (Uday Rao, Amitabh Raturi) In this project, we applied multiple linear regression, univariate linear regression, random forest, XGBoost, and Artificial Neural Network, models. Utilizing these two LASSO variables, Random Forest had the best out-of-sample accuracy at 72%. The purpose of this simulation study is to analyze the current emergency call-center system and data for the City of Cincinnati and simulate alternate systems. Moving forward, I will discuss rules extraction, genetic ensemble, and some visualization techniques to extract accurate but comprehensible rules from opaque predictive models. I was able to find out the best model to predict customers’ behavior, help the company reduce the loss. Various statistical methods have been used to find the best model as per the data. Future steps in the project will include completing current work and the modules in process and engaging in the Portfolio Construction and Trading modules. Missing values in the dataset constituted to about 30% of the observations. In this project we are trying to recreate their existing trip type classification with a limited number of features. Through this project we designed an analytical framework which takes ratings/reviews datasets as input, performs modeling techniques like regression, decision trees, random forest and gradient boosting machines, identifies the best performing model and outputs features which are important in driving the ratings. For the project a particular retail chain was considered, which have stores throughout the country. I have personally observed a negative impact on one of my past employer’s performance because of employee attrition. However, the stock market has high volatility which makes the price movements hard to be predicted. Once the variables are selected we build a model using these variables to predict the dependent variable. The project analyzed the potential of adding cash as an additional payment feature to more markets. BigMart(name changed) is a supermarket that could benefit from being able to predict what are the properties of products and stores which play a key role in increasing their sales. Hasnaa Agouzoul, Green Driveway Survey: A Consumer Research Study Based on Discrete Choice Modeling, March 11, 2010 (David Curry, Yan Yu) The modeling approach explored in this project is one amongst a suite of Bayesian probabilistic models popularly known as the Buy till you die models for estimating customer value. The results suggest that the logistic regression model has better predictive performance than does the tree model, and application preference, age, test score, home distance, amount of financial aid, and high-school type are crucial factors for applicants' choices. shopper expectations, channel proliferation, trip erosion etc. Supply uncertainty is widespread and has significant impact on business operations, so it is receiving increased attention by both industry and academia. An application using real call data from the City of Cincinnati is presented. Juan Tan, DrugBank Data Mining –  Wrangling & Network Analysis, August 2020, (Leonardo Lozano, Denise White). To answer the question, this project looks at existing credit consumers through the lens of their shopping history. In this capstone case, the significance of main female characters in a select list of Disney Princess title movies are explored by only comparing their scripts in those movies to that of the other main character, which is always not female, in each title. They don't require any assumptions between independent and dependent variables and work in non-linear environment. The dataset contains 50,000 records of the application information from the credit card applicants. This is a problem faced by a digital arm of a bank. It turned out that the negative-binomial regression model outperformed the Poisson regression model in this case. Beth Hilbert, Promotions: Impact of Mailer and Display Location on Kroger Purchases, July 2019, (Charles Sox, Yan Yu) Dota2 is a free-to-play multiplayer online battle arena (MOBA) video game. From a decision-theoretic point of view, a realistic loss function should be asymmetric (failure to choose good prospects carries a higher penalty than including too many bad prospects). Shubham Gupta, Text Analytics: Predicting product recommendation by customers based on the reviews, August 2020, (Leonardo Lozano, Peng Wang). Organizations have a constant need to assess where they stand day-in and day-out and where they can improve. In the last 2 decades, the e-commerce industry has consistently leveraged data to improve sales, advertisement and customer experience. Chaitra Nayini, Using Visual Analytics and Dynamic Regression Modeling to Forecast Trends and Optimize Station Capacity for a Bike Share Service, April 2015, (Yichen Qin, Jeffrey Camm) In a previous group case study, we developed a best model we believed contains the critical predictors for the policy renewal variable, and also generated a pricing elasticity curve. Gradient Boosting performed best out of the selected models. The objectives of this study were 1) to calculate national estimates of the annual burden of inpatient hospitalizations of children and adolescents with BPD, where burden is measured specifically in terms of charges, cost, and length of stay; 2) to describe and compare the burden across various demographic characteristics, hospital characteristics, and key comorbidities associated with BPD; and 3) to determine the independent effects of these demographic, hospital-type, and comorbidity factors on hospitalization costs. They are Poisson regression and negative binomial regression. The data for this project is taken from IBM sample datasets. The focus of the analysis will be on how the actual amount of precipitation on any day, affects the visitor count and whether it has an effect on one or two days after as well. CCHMC currently uses a manual scheduling method based on legacy schedules and each specialty maintains its own schedule. The classification and regression tree model was the least stable. A singular value decomposition technique decomposes a matrix into a product of three component vectors. Based on this increasing rate, the simulation results show that within five years the dispatch-to-arrival time will increase by 20 seconds (5.6% of the criterion), and in ten years the increase will be 62 seconds (17% of the criterion). The second model turned out to be more robust and it is very simple and easy to replicate this model in other statistical software. We show that the optimal production inflation rate, defined as suppliers' planned production quantities over retailers' order quantities, is dependent only on the wholesale price and is independent of the retailer's order quantity. Through the use of this data we aim to do the following: 1. Additionally, I developed methods to visually represent the SharePoint Report, including in PDF and URL formats, and to streamline the SCRUB process. It is an unsupervised algorithm that used the document corpus matrix to identify the most relevant topic related to the document. The baseline of this project is to develop a prototype solution for retailers, which allows them to provide a better product assortment to meet the unique preferences of their customers. The data is first introduced, a data dictionary is created for the reader to further understand the data, the data is then cleaned, and then some initial exploratory analysis is done. An analysis of individual firms’ financial dynamics is performed using their return on assets (ROA), operational dynamics using a sales by inventory ratio (SalesByInv), and resource-deployment or capacity utilization dynamics using a sales by property plant and equipment ratio (SalesByPpe), by treating them as continuous functional data during these time periods. This was done to ensure the process is scalable and reusable. Three time-varying regression coefficients are interpreted as level, slope, and curvature-factor loadings of the yield curve. The top problem type names, area of aircraft, hour and day with highest requests have been identified. Vidhi Bansal, Bike Rental Prediction Analysis, August 2020 (Yan Yu, Dungang Liu). Ten financial variables are adopted to build models for bankruptcy predictions. This paper re-examines research data of audio speech variables from recordings of three groups: 1) healthy controls, 2) patients newly diagnosed with PD and 3) an at-risk group. Then, we explored the potential information loss of binning in the development of several models using R, including logistic regression, classification tree and random forest. Using this method on metrics which closely depict their growth potential and customer behavior, the contributing companies are segmented into different clusters which would help UWGC better understand their contributors and better plan their contributor campaigns. QBR is a Quarterly Business Report which is presented to board members of the company. There are more than 587 conversations that happened between child predators and Pseudo-victims. After exploratory data analysis, logistic regression, lasso, support vector machines and random forest models are built on training data. By calculating costs and feasible arcs outside of the optimization solution stage, a simple transportation problem is created with fast run times and implementable results. The purpose of this project is to explore the sentiments of the user base and thereby explore the reasons why Windows 10 is not getting the traction targeted by Microsoft. This will offer insight into how teams might approach an upcoming game versus an opponent based on their attributes. In general, wearing a knee brace is helpful in preventing an MCL knee injury. Xiaoyu Zhu, The Comprehensive Capital Analysis and Review, August 2015, (Peng Wang, Yichen Qin) Shikha Shukla, Grocery Analytics: Analysis of Consumer Buying Behavior, July 2016, (Christopher Leary, Dungang Liu) Tracker system is an internal system in Boeing which records requests from employees working on the floor. National estimates of the means and standard error of the mean for cost, charges, and length of stay, for inpatient pediatric bipolar disorder (BPD) used the complex sample design of the 2003 and 2006 KID data, which contains weighting, stratification, and clustering variables. Retail Banking is a competitive arena focused on customer-centric service. Stratified random sampling design and Neyman allocation are used to design the capital-expenditure survey. Having a customized pricing policy based on the characteristics of each segment can potentially enhance sales and thus maximize profits by extracting the complete value created by the product for the different segments. In this paper, we use simulation and probabilistic techniques along with queueing theory models to investigate the relationship between service level of severely obese patients and the number of bariatric rooms needed to reach a designated service level with such patients. The number of days of rest between games, the number of time zones from home, the number of time zones from the previous game, being home or away, and traveling after a day or night game were tested as independent variables to correlate with the dependent variable of winning or losing a game. Historical delivery point locations and vehicle-related costs are collected from the company. The problem is based on a competition now closed on Kaggle. This paper introduces two predictive models: a logistic regression model and a classification-tree model, to unveil the association between offer acceptance and applicants' personal information, application and financial aid. Credit scoring is one of the data-mining research areas, and is commonly used by banks and credit-card companies. To overcome this problem, stratified sampling, random under and over sampling, SMOTE and ADASYN methodologies were explored. LSI finds ‘topics’ in reviews, which are words having similar meanings or words occurring in a similar context. This is further fueled by the increase in the number of retailers and thereby the competition. The project involves analyzing customer data for an insurance company. Shixie Li, Credit Card Fraud Detection Analysis: Over sampling and under sampling of imbalanced data, November 2017, (Yichen Qin, Dungang Liu) As a crowdfunding platform, Kickstarter promotes projects across multiple categories such as film, music, comics, journalism, games and technology, among others. The variability and mean of each upcoming play can then be weighed and considered from this model. How to use the non-parametric survival analysis and parametric survival analysis with different distributions to create models for the survival object will be discussed. Phase two analyzed collected data using a latent-class approach to discrete-choice modeling. These exceptions are only applied to cancel requests that fall under Priceline’s predefined categories/cancel reasons. The study was based on Linear Regression and Regression Trees since interpretability of the model is of the most importance, hence complex models were not explored. Priceline offers lower rates to its customers on certain deals which are non-cancellable by policy. Analysis of the different features of subscriber base (approximately 10 million per month for a period of 29 months) like credit class, Regions, Devices, etc. Based on this information, the client can plan their marketing campaigns more cost-effectively. A wage gap does not exist for all females across all industries, so in my extended research, I worked to narrow the focus to the industries, age groups, and locations that have the most prevalent wage gaps and what the reasons for those wage gaps may be. Shaonan Tian, Data Sample Selection Issues for Bankruptcy Prediction, August 12, 2009 (Yan Yu, Martin Levy) The first problem we attack is how to help increase sales. More than 50 predictors were considered in the model, including account-application data, performance data, credit-bureau data, and economic data. Generalized linear modeling and mixed effect modeling demonstrate similar performance without obvious over fitting. Akshay Mahesh Jain, Customer Segmentation and Profiling, November 30, 2012 (David Rogers, Edward Winkofsky) The most frequent word appeared in the dataset is patient, and the most frequent word appeared in the dataset with dissatisfied review is impatient. Amongst these classifiers, Gradient boosting was observed to have the best performance, although with further fine tuning, Deep Neural Networks could possibly classify better. Products are delivered between sites by trucks. Among the decisions with the greatest implications for airlines' profitability are fleet assignment and the methods used for passenger ticket distribution. Arathi Nair, Demand Forecasting for Low-Volume, High-Variability Industrial Safety Products under Seasonality and Trend, December 4, 2013 (Uday Rao, David Kelton) Knowing one’s income can also assist an individual in financial budgeting and tax return calculations. The train set contains 60,000 labeled images and the test set contains 10,000. Using several years of survey data provided by the Kenton County Alliance, the main factors which influenced the use of alcohol, cigarettes, marijuana, and inhalants were determined using several techniques – classification trees, chi-squared automatic interaction detection (CHAID), and logistic regression. This data includes information about the candidates regarding their status of 2 protected classes : Currently, the proportion of employees belonging to these protected classes in the University of Cincinnati are significantly lower across most job groups and business units, compared to the proportions in relevant pools provided by the U.S. Department of Labor. The email text data is analyzed using natural language processing techniques and then using machine learning algorithms, segregated into the correct ticket type. Among 10,000 plants selected in this study, 711 completed the survey and sent it back to the Gardner's Publication. In an effort to reduce the distribution costs from distribution centers to the customer location a company is considering opening a set of five distribution centers to cater all of its customer locations. Hamed Namavari, Disney Princess: Strong and Happy or Weak and Sad, A Sentiment Analysis of Seven Disney Princess Films, December 2016, (Michael Fry, Jeffrey Shaffer) New weights from parameter coefficients of regression models ran in the original case study will be derived and evaluated. Since a significant part of that energy is consumed by household sector, the optimal consumption of the energy at home is of great importance. The increase in the obese population of the United States along with high costs for bariatric beds and dedicated bariatric rooms have necessitated investigating a better way to determine the proper number of bariatric rooms to construct, bariatric beds to own, and bariatric beds to rent. University Hospital's Emergency Department (ED) treats nearly 100,000 patients annually. A special focus is given on ensemble models during the study. A pressure injury is defined by NPUAP as "localized damage to the skin and/or underlying soft tissue usually over a bony prominence or related to a medical or another device. The performance of the SRFS in terms of the number of columns and nodes created to arrive at a solution was also investigated. According to US Energy Information Administration, the share of renewable energy could rise from 13% in 2011 to up to 31% in 2040. A significant amount of time has been spent setting up the dataset before the modeling process. The Conversation AI team[1], a research group founded by Jigsaw[2] and Google builds the technology to protect such voices. The findings, using AMPL and CPLEX as a solver, showed that the fewer resources employed, the longer it took for a solution to be found. Recommender systems are used widely, in order to help users accessing the Internet, by suggesting the products or services, they would be interested in based on their historical behavior, as well as the behavior of other users similar to them. To understand the customer behavior a coupon-redemption study was carried out by the company. Over the past five years, 33 different special events have been hosted. The data in this project is collected from Kaggle. The second project uses SAS programming to manipulate the performance data of a call center that has operations in multiple sites and business areas, and to help analyze its improvement in terms of AHT (average handling time, a metric to measure the time a representative spends handling an inbound call). With 2016 elections data, the never-change-vote model found that Income, Age, Ideology, News and Married status were significant to this never-change-vote behavior. Recommendation systems can enhance customer engagement by not only providing selective offers which can be highly appealing to the customer but also by adopting targeted marketing and advertising efforts towards potential customer segments and thereby achieving cost efficiency. Consequently, I found out the trend of sales price in real estate industry is organized and predictable. Xiaoning Guo, A Comparison of Data-Mining Methods in Direct Marketing, December 7,2012 (Martin Levy, Yan Yu) Demand forecasting is done using different time series models like Exponential Smoothing, Croston’s Method of Intermittent Demand Forecasting, ARIMA and error measure used is WMAPE and RMSE to compare the models. In this research project, two popular bankruptcy forecasting models, Shumway (2001) Simple Hazard Model and Logistic Regression Model, are studied and compared. This project also predicts the top 5 recommended movies per user based on their historical ratings from the Movielens database. A collaborative filtering algorithm could pose the problem of data sparsity. This article examines the pervasiveness of phony news considering the advances in correspondence made conceivable by the rise of person to person communication locales. The sum of the weighted count of these violations provides a driver’s score. It depends on a lot on non-quantifiable metrics. The objective of this project is to analyze reviews on Yelp for restaurants using text mining and sentiment analysis using Python to understand how many reviews expressed positive or negative sentiments about the food and the service, and what they had to say about them. Variable reduction for the first logistic model built was done using stepwise logistic regression based on AIC criteria. Of the different classification techniques that were built and tested for performance, the logistic regression model was found to be the best performing, with the highest accuracy of 84.63% in predicting the income level of an individual. Content-based Filtering, Knowledge-based, Collaborative Filtering and Hybrid filtering are the widely used recommender system techniques. This project aims to create a tool that recommends the optimal price to maximize profit by using historic sales data and the price elasticity of demand for top selling items within each state in which EG America operates. The purpose of this analysis is to give insight into which 2016 rookie wide receivers are in the best position to have success in their rookie season and would validate being selected early in dynasty football drafts. This project uses a Random Search algorithm paired with a Monte Carlo simulation study in order to find “Optimal” Catastrophe Reinsurance structures. The results of analysis were used to build dashboards in Tableau. The SEDEA model, implemented in R, uses cost and quality measures for each hospital to calculate the hospital efficiency scores and ranks the hospitals accordingly. The hospital management finds difficulty in manually deriving a nurse roster for a six-week period while trying to place an adequate number of nurses in the emergency-care unit of the hospital. With the automated process of renting a bike on an as needed basis makes it very convenient for the consumers to rent a bike. The completion and service level agreement (SLA) compliance rate for IEN (Intelligence Engineering Network) projects at Verizon is lower than desired. By analysing users reviews, a company can be aware of how its users feel. For this Capstone we used Logistic Regression and Classification trees. Section 2 concentrates on the exploratory data analysis of the data set to obtain the overview of distribution of price premium and physicians. Apoorv Agarwal, Privacy Preserving Data Mining: Comparing Classification Techniques while Maintaining Data Anonymity, April 2016, (Dungang Liu, Peng Wang) The forecasted value from the ARIMA error with the linear regression equation gave us the final value for the daily customer arrival. According to the CDC, the number of people diagnosed with diabetes increased fourfold from 1980 to 2014. Mudit Verma, Customer Churn Modeling for Term Policies at Ameritas, August 2020 ( Dungang Liu, Jennifer Kelly). The second methodology is creating a prediction model for overall plant energy usage based on historical data. After the analysis it is clear that the P credit class in spite of making the maximum number of claims has the lowest incident rate. In the fight against online pedophiles and predators, a non-profit organization named Perverted-Justice has pioneered an innovative program to identify child predators by pretending to be a victim. The optimized trade payout generated in the process ensures that the investment encourages the decisions taken by the retailers that favors the manufactures, while not penalizing poor outcomes beyond what is necessary. was done to understand the relationship between incident rate and subscriber features. Antibodies are a critical and perishable inventory component for the operations of the Diagnostic Immunology Laboratory (DIL) and require time-intensive quality validations upon receipt. The purpose of this paper is to explore and quantify the effectiveness of wearing a knee brace vs. not wearing a brace in preventing motorcycling knee injuries, by providing statistical analysis on the questionnaire data. Previous theoretical studies of ensembles have shown that one of the key reasons for this performance is diversity among ensemble models. Solving this CAPTCHA is not very easy and sometimes the user gets frustrated in this process. This will help in increased understanding of the report and the better usage of the product details for further analysis. The Brand Actualization study at FRCH | Design Worldwide was intended to evaluate ratings of various brands and build a model for brand assessment. Finally, the seasonal component of energy profiles were used to cluster customers based on family lifestyle patterns. This project leverages data from a Kaggle competition where 42000 labeled samples of numbers were given and participants must build models which could accurately recognize numbers from 0 to 9. Since financial aid is the only factor that the school can control in admission, the allocation of limited financial aid is necessary to attract ideal applicants. Objective of study was to develop predictive model to identify the variables responsible for churn of customers and predict potential customers which may churn out of telecom services. The dataset on Kaggle had two data sets: one for training the model, this dataset had 100,514 observations and the testing dataset had 10353 observations. The objective of this exercise is to analyze the browsing behavior data of online visitors, in order to predict the success of purchase for each visitor. and analysis of the different features of the fulfilled claims per month base (approximately 115 thousand per month for a period of 29 months) like day of week, tenure, etc. The goal of this study is to model the bankruptcy probabilities of seven major banks under different economic scenarios. Anvita Shashidhar, Data Warehouse and Dashboard Design for a Hospital Asset Management System, July 2015, (Andrew Harrison, Brett Harnett) All conclusions drawn from this research are justified by proper statistical analysis. Classification and regression trees (CART), an alternative methodology, is also applied to help fit the model. The probability of default is modelled as a logistic curve whose parameters are determined based on historical data. While there are a large number of methods available, not all of them are applicable to categorical data. Connect instantly with local businesses, browse menus, search by cuisine, book a table, see showtimes, and find cheap gas. These physicochemical properties can be used to model wine quality. Analytical tools are used to perform a thorough data exploration that leads us to key insights that would be beneficial in the modeling process. The objective of this study is to use the energy data to build a model that can predict the Energy Star Score of a building and interpret the results to find the factors which influence the score. To achieve this objective, regression models were built to represent the relationship between customer experience and their basic information. Used car dealers often buy cars from auctions which sometimes do not allow a thorough inspection of the vehicle before the purchase.

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