As in our case prediction is our major concern, the random forest model was chosen as it had the best prediction for the Diagnosis of breast cancer cells. The objective of this project is to optimize the process of diagnosis and resolution of issues with various products faced by the customers of one of world’s largest technology companies and addressed by tech support agents. Booking pattern has been analyzed in this project across 365/366 days of the year. Based on this information, the client can plan their marketing campaigns more cost-effectively. It serves to reduce variation in a Primary Insurance company’s financial statements, to transfer risk to a Reinsurance company and can maintain financial ratios that are either required by law or desired by shareholders. However, for finalizing a model only metrics from the test dataset were used. It is extremely difficult to predict exactly how well pilots will perform in the cockpit. The generally acknowledged meaning of Internet fake news is: imaginary articles intentionally manufactured to trick readers. It also indicated that on bad weather days the attendance drops by 25% on average. Addressing these factors could then potentially save lives, prevent long-term pain and suffering, and avert liabilities and monetary damages. Currently Qubole does not have one single reporting platform where all the important metrics are tracked. This complexity of the data clearly shows the limitations of the ARIMA and SARIMA. 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. The project is all about customers which are churning in a telecom industry. Some of the benefits of this system if implemented were that Schwab would be: The desired system will not only help the team in monitoring but also the development team to understand the performance of the application and the infrastructure management team to understand the amount of server usage for capacity planning. An approach to minimizing patient waiting, staff idle time, and total duration at a clinic is to develop a MILP model that optimally schedules tasks of the clinic's staff members. If the actual purchase does not happen because of any reason, seller has to be refunded the fee amount as a credit. Finally, we compare the in-sample and out-of-sample model fits with different choices of shape parameters. In Zoo business it is very important to know in advance about the arrival patterns of the customers across various months. For case studies, the client firms outline the business problem, provide datasets for graduate students to analyze, and upon completion of case study projects both clients and students submit feedback forms. The supply and consumption of renewable energy resources is expected to increase significantly over the next couple of decades. I cleaned the data set, input missing values, conducted exploratory analysis and built two nonlinear regression models: Random Forest and Gradient Boosting to predict housing price. The cutoff value should be chosen within the region or around the region and it is all depends on whether precision or recall is more important to the bank. Data Science and Analytics is widely used in the retail industry. Fraudulent transactions after card hacking is becoming a major concern for credit card industries. Numerous applications can be visualized from such activity analysis for instance, in patient management, rehabilitation, personnel security, and preemptive scenarios. The resolution time and in fact, the requests directly impact the aircraft assembling process. It is discovered that the age and financial status are the largest and most important differentiators for the two population groups. Jing Gao, Patient Satisfaction Rating Prediction Based on Multiple Models, August 2017, (Peng Wang, Liwei Chen) CCHMC currently uses a manual scheduling method based on legacy schedules and each specialty maintains its own schedule. Mauricio Pochettino admits it will be difficult for PSG to win the Ligue 1 title this season following their home defeat to league leaders Lille. More than 50 predictors were considered in the model, including account-application data, performance data, credit-bureau data, and economic data. Logistic regression is the approach used in this project considering the dichotomous nature of the dependent variable. Customers who visited recently on the website, had more recent orders, had items Added to Cart and higher overall purchase per month are more likely to purchase a product in the next month. Simulation has been used extensively in the manufacturing world; however, there are many untapped opportunities within the world of health care. The idea behind customer targeting is to optimize targeting so that one targets the right kind of customer at the right time, with the right kind of product in order to maximize sales, save business resources and maximize profit. This project is an ad-hoc predictive analysis to determine the target customers for a Paper Towel producing CPG brand, (say YZ) targeting its customers with personalized coupon offers for various retailers. Furthermore, machine learning techniques such as Logistic regression, Classification tree, Random forests, and Support Vector Machine were used to predict the income level and subsequently identify the model that most accurately predicted the income level of an individual. Concession and Merchandise sales account for a substantial percentage of revenue for the Cincinnati Reds. Online retailers in the world who happen to have a small business and are new entrants in the market are keen on using data mining and business intelligence techniques to better understand existing and potential customer base. An effective underwriting and loan approval process is a key predecessor to favorable portfolio quality, and a main task of the function is to avoid as many undue risks as possible. Great American Insurance Group (GAIG) writes a significant portion of its business in workers compensation. Also, logistic regression and Random forest techniques have been used to predict the negative sentiments. This is where the recommendation systems come into play. Surya Ghimire, Forest-Cover Change: An Application of Logistic Regression and Multi-Layer Neural Networks to a Case Study from the Terai Region of Nepal, July 2, 2010 (Yan Yu, Uday Rao) Archbishop Moeller High School has an ambitious plan to increase its participation rate (giving + activities), up from 4% a few years ago to 13% last year with a goal of 15%. Priyanka Pavithran, Blindness Detection in Diabetic patients – using Deep Learning, August 2020, (Yan Yu, Liwei Chen). We went through great lengths to create a system that could fully accommodate multiple comms systems. A working optimization model was developed to provide educators with a useful tool for addressing their changing needs. As the output variable (dependent) is an ordered (or categorical) set, we considered using ordinal and multinomial logistic regression. 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. Tathagat Kumar, Market Basket Analysis and Association Rules for Instacart Orders, June 2018, (Yichen Qin, Yan Yu) The method is then evaluated using samples of correlated Weibull variables. Each subscriber is nuanced in what brings them joy and how that varies based on the context they are set in. There are multiple reasons why patients do not take medication on a timely basis. This information was extracted from ‘purpose’ column in the data. This report gives a brief overview of the two retailer specific targeting campaigns designed for the biggest yogurt brand and personal care products brand in its vertical. The study also explores attributes of visitors requesting more information through the website. Effective issue prioritization could result in more issues investigated, quality improvements, improved early detection, and potentially a reduction in warranty claims. The data was collected from the UCI Machine Learning repository. Packages were built in SSIS to automate these tasks and the resultant data sets can be viewed and analyzed through reports built using SSRS. In my project, I have discussed how we can predict all the genres associated with a movie just by looking at the plot of the movie with the help of NLP and multi-label classification using algorithms like Naïve Bayes and Support Vector Machines. The models are then evaluated using ROC curve and precision-recall plots for a different number of recommendations. However, with the platform’s ever-growing popularity, many users submit similar questions. Oil Prices can depend on many factors leading to a volatile market. The dataset was obtained from Kaggle [10]. Further, I have explored different sampling techniques such as Over Sampling, Under Sampling, SMOTE, etc. Moreover, number of features range, generally from 10 to 20 and hence a linear distance metric, often, do not give good results. Human resources plays an important part of developing and making a company or an organization. The structural breaks have been searched with a practitioner approach based on the time series modeling minimal regression RSS (Residual sum of squares) which is described in this paper (hereinafter referred to as “Minimum RSS search”). What should the premium be of the products it wants to insure? Measures like classification percentage, misclassification rate and misclassification cost will be used to evaluate the models. The model employs techniques from computer vision and Natural Language Processing (NLP) to extract comprehensive textual information about the given images. It is extremely important to characterize a player according to their position on the field. This data contains important information about customer profile, demographic information, technology used, user patterns, consumer trends etc. A staggering 33% of American adults are obese and, as a result, obesity-related deaths have climbed to more than 300,000 a year. Asset pricing is one of the most researched areas in investment management. The results show that the robust optimization model performs the best in terms of stability. Models were built using voter registration and history and demographic information from the U.S. Census and Social Security Administration. However, as this product is first of its kind in the market, getting actual customer data isn't possible. All the models are built using the ‘sklearn’ package in Python. If an account does not charge off, the late fees associated with that account are assessed as a profit for the company since the money will be collected. Shriya Sunil Kabade, Customer Churn Analysis, July 2019, (Dungang Liu, Liwei Chen) Two main types of collaborative filtering i.e., user based, and item-based methods are used here. The autocorrelation function/partial autocorrelation function plots were used to examine the adequacy of the model as well as Akaike Information Criterion (AIC). delivery times of previous purchases, product description, product photos etc. While the number of both subscribers and single ticket buyers is decreasing year by year, the number of single ticket buyer is not decreasing as rapidly as it is of subscribers. However, among potential customers, some customers would purchase regardless of any marketing incentive while some customers would purchase only because of marketing contact. As a part of Data and Applications Vertical and Wallet Analysis Team, my primary objective was to study the concepts of Record Linkage, Identity Resolution and to develop an algorithm to identify the unique customers from different data Sources and to populate into a single normalized flat database using deterministic Record Linkage process for the UK market. For the case study, we intended to use linear regression to determine which categories of driving violation, as specified by Great American’s underwriters, had the most impact on the loss ratio and use those findings to create a scoring system for drivers or policies. The unsuccessful students are defined as students enrolled in a program for more than 6 years and didn't graduate. Using publically available data, I attempt to compute the cost-minimizing rebalancing plan for the bicycle sharing system that services the Washington DC area. This project provides a measure of efficiency by performing a super-efficiency data-envelopment analysis (SEDEA) on hospitals from Ohio and Kentucky that perform percutaneous cardiovascular surgery with drug-eluting stents. Then, multiple predictive statistical models are built in order to predict the possibility of an employee leaving the firm and factors were studied by plotting variable importance. I used the matches of 2014 for the system to learn and then predict the results of all 127 matches of the 2015 Australian Open. The value proposition of the customized products is very different from a commodity product. Usually, any insurance company has a few questions to answer before insuring any product. Premier League is a soccer league filled with rumors, sources, news, and critics. Venu Silvanose, Developing and Assessing a Multiple Logistic Regression Model on Mortgage Data to Determine the Association of Different Predictor Variables and Borrower Default, June 3, 2009 (Martin Levy, Norman Bruvold, Yan Yu) Concrete is so ubiquitous today that it is often taken for granted. After extensive research, results showed #1 hits have steadily gotten more repetitive over time, as popular songs have had a declining lexical density and increasing compression ratios. Rohit Pradeep Jain, Image Classification: Identifying the object in a picture, July 2018, (Yichen Qin, Liwei Chen) Two types of ensemble learning procedures, random forest algorithm and gradient-boosted trees, were attempted. Cost curves are developed for these various scenarios to provide graphical support of the effects and tradeoffs inventory system decisions can have on total costs. The final feature set including both base variables and derived variables was used to shortlist the factors affecting the rise in cases and the associated weightage for each of the factors. It is a text analysis method to determine the polarity within the text, a whole document, a sentence, or a paragraph. America is home to some of the most obese people in the world. If the right message is sent to the right group, it can help increase customer engagement and help generate higher profits at a lower cost. A mixed-integer linear-programming model was solved to provide the optimal Divisions to minimize the average travel distance while keeping a balance of ranking and travel between the Divisions. Positive reviews boost the confidence of an organization while Negative reviews suggest areas of improvement. A higher rating given to a product might increase the trust in the same and can motivate other customers to make a purchase. The data in the database is entered by each project manager and relies on accurate and up-to-date entries. Valuable information regarding process performance is contained in these data histories but they are seldom tapped to their fullest potential. The industry has realized the need for strengthening the relationship with their customers. This project is an examination of five different reallocation time periods applied to a long-only equities portfolio, for which the assumption is made that you can only buy assets to include and no short positions are allowed. The new method named Cluster-LASSO linear regression model has been developed by combining nonparametric clustering and LASSO linear regression methods. Customers interacting with banks through multiple channels have created an explosion of data, banks use to generate insights into their behaviors. Pricing analytics is at the core of profitability, but setting the right price to maximize profits is often difficult and extremely complex. Subcontracts are costly and hence need to be avoided, if possible. This project uses different machine learning algorithms to diagnose cancer into benign or malignant type. SMOTE stands for Synthetic Minority Oversampling Technique, a process in which synthetic instances are generated from the minority feature space to offset the imbalance. Julian Green got 35 minutes or so for Bayern in the Pokal today. The customers are classified into different segments and current pricing benchmarks are obtained for each segment. It is important that engineers do not miss potential urgent or high-customer-impact items because excellent customer service is expected. Various statistical methods have been used to find the best model as per the data. In this project we build models using three data mining techniques namely Logistic Regression, Decision Trees and Linear Discriminant Analysis. The data was reviewed for the time period of 1/1/2020 to 6/22/2020 and included 60 workouts prior to the gyms closing, 50 at-home exercises, and 3 workouts back at the gym after the gyms reopened (this data was excluded as there were not enough data points to form a trend). Especially, Random forest is an extension of Bagging, but it makes significant improvement in terms of prediction. The goal of the project is to predict the churn rate of the customers for one the telecommunication client. Over recent years, the utilization of antidepressant drugs in the form of doctors' prescriptions and Medicaid reimbursements has been rising steadily. The final trained model showed an accuracy of 96.2% with most of the error happening in cargo and carrier. But the star rating may not capture the entire sentiment of a customer about a product. Survival analysis, also called time-to-event analysis, primarily was used in the biomedical-science area to observe the time to death, now also widely used on other analyses such as the working life of machines. Data sources and outputs are designed to easily connect with a "real-world" platform. China has experienced rapid economic growth which benefited many industries but not the healthcare system. The first project evaluates the impact of new QCUH factor from revenue standpoint. The Commercial banking business deals with many customers that buy various products from the bank. While this process works well for most SNPs, a small portion equating to thousands of SNPs is problematic. We also predict the expected revenue for each zip code across United States. Hierarchical clustering analysis is used to segment the dataset to find classes of firms that demonstrate similar patterns in terms of their performance. The intersection of North Bend Road and Edger Drive is under constant scrutiny by drivers who get stuck in long queues while waiting on Edger to turn onto North Bend. The report discusses the theory and application of a combination of Beta Geometric Negative Binomial Distribution (BG/NBD) model and the Gamma-Gamma submodel for estimating the expected future value of customers for an e-commerce retail business. The literature about simulation of retail pharmacies is scarce, though. Currently, we are generating more reports based on this one as clients are doing some deep-dives. The applications of deep learning have achieved great success in the healthcare industry in recent years. Identifying customers who are more likely to respond to a product offering is an important issue in direct marketing. Supply Chain Management has been an area of interest among businesses that seek efficiencies and cost-saving opportunities in this area. Vivek Sahoo, Dashboards as a Product Offering & for tracking Product Usage, August 2020, (Michael Fry, Christy Foxbower). This study is aimed at analyzing the profile of online mobile visitors, and recommending divisions with high mobile traffic for future web enhancements. While we have dedicated advisory services which advise on when the best time to buy tickets is, and if the current price is high or low based on historical data not a lot has been spoken on the various factors affecting the cost of flying from one destination to another. Telephone service companies, Internet service providers, pay TV companies, insurance firms, and alarm monitoring services, often use customer attrition analysis and customer attrition rates as one of their key business metrics because the cost of retaining an existing customer is far less than acquiring a new one. When a different company owns or guarantees for a company, the latter’s direct exposure also shows up as indirect exposure for the former. Hierarchical clustering was used to label brands with distinct clusters. It is considering tapping the available amount of data in order to optimize its sales and increase margin. What are the products it should insure? Obtaining the attention and interest of a shopper can be extremely difficult, nonetheless so when a credit card is being promoted by a retailer whose marketing budget does not stand up to those of larger banks. The main aim of this project was inference based. Conversational toxicity is defined as anything rude, disrespectful or otherwise likely to make someone leave a discussion. November 2020 27. The balance sheet, income, and bankruptcy risk are analyzed so that their capital status, operation risks and default probabilities are evaluated. Peipei Yuan, Stratified Random Sampling Design for Capital Expenditure Survey, March 15, 2013 (Martin Levy, Yan Yu) For example, It can send alerts and targeted offerings and provide insights that help banks to develop direct marketing campaigns. Swidle Remedios, Analysis of Customer Rebook Pattern for Refund Policy Optimization, July 2018, (Michael Fry, Antonio Lannes Filho) Neha Nagpal, Predicting Dengue Disease Spread, July 2019, (Dungang Liu, Chuck Sox) Presently, Cincinnati Zoo expects customer arrival on a particular day totally based on historic customer arrival. This project explores the AMES Housing Dataset which contains information on the residential property sales that occurred in Ames, Ohio from 2006 to 2010. A lot of players are injured, he wont get much playing time if everyones fit. Model diagnostics are conducted. The study determines the viability of crack sealing on different pavement conditions and quantifies the improvement in age resulting from the crack-seal process. 2. The train set contains 60,000 labeled images and the test set contains 10,000. Gauging a product’s demand and performance has always been a difficult task for retailers. The daily operational task of assigning empty freight cars to serve customer demand is a complex, detailed problem that affects customer service levels, transportation costs, and the operations of a railroad. Due to the high dimensionality of the data and less number of observations I used lasso subset selection with cross-validation to reduce the number of predictors. This is a problem for citizens across the globe because the availability of resources per individual is decreasing by the hour as population keeps increasing. This project explores different ways to forecast unit sales of products with the objective of zeroing in on the model with the least error. AUC and misclassification rate are calculated on the training and test datasets. Many carriers have started working on SMS spam by allowing subscribers to report spam and taking action after appropriate investigation. By analyzing win shares, one measure of an individual player’s offensive efficiency, we can better project the value each draft selection will provide to their team. The patterns identified in the Data exploration stage were used as inputs in for predictive modeling. The process involves fetching data from the Catalyst Reporting Tool (CaRT) using queries and then creating the required input file for Tableau dashboard through data manipulation using SAS. A hybrid recommendation model combining the product features (Content Based Recommendation) and the performance of the products (Collaborative Filtering model) has been developed. Shivaram Prakash, Predicting online Purchases Navistone®, August 2016, (Efrain Torres, Dungang Liu) Performing correlation analysis showed that Insulin and Glucose, BMI and Skin Thickness had a moderately high linear correlation. Company A is a national engineering consulting firm that provides multi-media services within four distinct disciplines: Environmental, Facilities, Geotechnical, and Materials. Dota 2 is played in matches between two teams of five players, with each team occupying and defending their own separate base on the map. Also, the crime index was disaggregated into violent crime and property crime, and regression models were built with these approaches to explore how different levels of aggregation affect the results. Identification of factors responsible for the pressure injury can be very difficult and is of vital importance for the hospital bed manufacturers. Churn propensity models can help improve the customer retention rate and hence increase revenue. Customer churn is the loss of customers. Tensorflow is a framework that relies a lot on computational power and hence higher accuracy could be obtained by tweaking the hyper parameters on state-of –the-art systems. 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. Data are from the open-source Carbo-Loading database available from 84.51°, which includes records from more than 5 million transactions for these items from two large U.S. geographical regions in which a large retailer operates. To understand the customer behavior a coupon-redemption study was carried out by the company. Some preprocessing is done on the data to prepare for analysis and modeling. The data will have de-identified variables and observations. Various predictive models were explored and their performance were evaluated to determine the best model. Several scenarios were examined to analyze the potential effects of increased traffic through the intersection. Huiqing Li, Statistical Analysis of Knee Bracing Efficacy in Off-road Motorcycling Knee Injuries, March 5, 2010 (Martin Levy, Yan Yu) The classification and regression tree model was the least stable. Manish Kumar, Intelligent Allocation of Safety Stock in Multi-item Inventory System to Increase Order Service Level and Order Fill Rate, June 3, 2009 (Amitabh Raturi, Michael Magazine) Summary statistics and interactive dashboards were created in Tableau to get insights on characteristics of 3 concentration areas and see how overlap and mismatch areas distributed. Also, there are cases where a transaction is taken off the website because of the mutual agreement between buyer and seller. This final model was then used to build an applicant default scorecard that has a range between 300 and 900. Widespread application of the inverse problem in medicine, mathematical physics, meteorology, and economics has attracted much research.
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