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. Emily Fischer, COVID-19 Impact on Strength Training, August 2020 (Leonardo Lozano, Alex Wolfe). The optimization model is based on seven conferences in total and ten teams in each conference. In this project we are performing credit scoring analysis on Australian credit scoring data. The linear model provided better results than the regression tree to predict the interest rate for the applicants. The primary macroeconomic drivers for 2nd Lien balance are Prime Rate, and All Transactions Home Price Index in Huntington footprint. Companies that serve customers or businesses at a large scale inevitably have customer service departments where valuable information is stored as free form text. The insurance industry tends to be very stagnant and resistant to change and new ideas. In our analysis, we explore various factors that can be included in the asset pricing model. Nitish Deshpande, Forecasting based impact analysis for internal events at the Cincinnati Zoo, April, 2015 (Craig Froehle, Jay Shan) World population is rising rapidly. Methods of analysis include (but not limited to) visualization of spread of different features, identifying correlation between covariates and the dependent variable and implementing different classification algorithms such as Logistic Regression, Decision Tree, SVM and Random Forest. The goal of this project is to build a recommendation system which will identify products most likely to be reordered by customers in a given order. This study is aimed at finding the next purchase of a customer given his current purchase. The comparison between the low-sale-price range and the other ranges in terms of the property tax underpaid/overpaid clearly indicates that the home owners of the low-sale-price houses are heavily taxed by the local government in an inappropriate manner. Rasesh Garg, Movie Recommender System, August 2020 (Michael Fry, Peng Wang). Krishna Kiran Duvvuri, Predicting the subscription of term deposit product of Portuguese bank, April 2015 (Jeffrey Camm, Peng Wang) I have used a text classification to classify news into two bins: true and fake. This parallel processing enables faster handling of large datasets and implementation of more complex machine learning algorithms for more accurate predictions. They also have significantly impacted businesses by increasing purchases resulting in increased revenue. This project explores the AMES Housing Dataset which contains information on the residential property sales that occurred in Ames, Ohio from 2006 to 2010. The challenges in the project include the inconsistent demand for less desired projects and shorter life span of the products due to the increasing need of innovative products in the market. 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. Using historical data, granular level demand models are created to anticipate price elasticity. In addition, Random Forest and Tree models are built in SAS Enterprise Miner and the random forest model with hour and neighborhood factors shows the best performance with the lowest misclassification rate (0.67). The year of sale and the neighborhood are entered as random effects and all other predictors are evaluated as fixed effects. Craft spirits are usually produced by small distilleries that use local ingredients. Joel Andrew Schickel, A Probit Classification Model for Credit Scoring Using Bayesian Analysis with MCMC Gibbs Sampling, August, 2015, (Jeffrey Mills, Martin Levy) Gauging a product’s demand and performance has always been a difficult task for retailers. Furthermore, by using the platform of Cytoscape, the drug-target, drug-enzyme, and drug-transporter networks are built and analyzed. Kenton Asbrock, The Price to Process: A Study of Recent Trends in Consumer-Based Processing Power and Pricing, April 2018, (Uday Rao, Jordan Crabbe) The System is set up in such a way that the whole process of obtaining membership, rental, and bike return is automated via a network of kiosk locations throughout a city. The algorithms used handles missing values on their own as they all are based on decision trees. The Convolutional Neural Network developed using the Keras library in python recognized alphabets corresponding to hand gesture with 98.3% accuracy. Himaja Gaddam, Analysis of Household Electric Power Consumption, August 2020, (Yichen Qin, Dungang Liu). Residual analysis has been conducted to identify the outlying and influential observations for each simple linear regression model. Credit risk modelling is the best way for lenders to understand how likely a loan is to get repaid. Streaming music have become one of the top sources of entertainment for millennials. The Convergys (CVG) Contact Center currently operates at three locations, one onshore in Erlanger, KY and two offshore in the Philippines and in India. I plan to try Regression, Decision Trees, Gradient Boosting and fit the best model to the data. FM Careers. A lot of players are injured, he wont get much playing time if everyones fit. Following which, the interactions between these variables were studied to weed out highly correlated variables. They currently have two Garden Center locations, a nursery and landscaping services. Ketan Kollipara, A Study of Scenario-Based Portfolio Optimization using Conditional Value-at-Risk, March 9, 2011 (Jeffrey Camm, Kipp Martin [Professor, Booth School of Business, University of Chicago]) 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. It consists of 44200 images (28 x 28-pixel data) of American Sign Language hand gestures corresponding to alphabets ranging from A to Z. Die Anmeldung und deine Fahrzeuginserate online sind völlig kostenlos. Even though the percent of a fraudulent transaction is very low in proportion to the total transactions, fraud transactions can hamper the consumer sentiment. which will improve current employee satisfaction levels. Acessórios e alimentação para animais, blogue animais. In general, there is little difference in the model performance for the original data and binning data, which means there is little information loss after binning the data. The aim of twitter analysis is to capture pulse of the people during this quarantine majorly positive or negative. In order to make sure this underserved population has a positive loan experience, Home Credit makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities. Therefore, it is chosen as the final model. To build the classification model, machine learning classification algorithms like Logistic Regression with Lasso regularization, Random Forest, Boosting, naïve Bayes classifiers and deep learning algorithms like Recurrent neural network using pretrained GloVe word embedding is used. Using forecasting techniques we can better understand the seasonalities and trends in the data. The root cause of the low compliance and low completion rate is not known. The capacitated vehicle-routing problem (CVRP) is a vehicle-routing problem to determine the optimal set of routes to be performed by a group of vehicles to meet the demand of a given set of customers or suppliers including vehicle-capacity restrictions. One of the primary challenges insurance and reinsurance companies face today is understanding catastrophe risk in a changing landscape. The data contains the information about the customers from the Indian Subcontinent. along with out-sample AUC are compared. This will facilitate high quality answers, and provide for better user experience on the platform. Nowadays, with the help of advanced technologies, the same can be achieved without human interference. The results using support vector machines (SVM) are promising: we achieve an accuracy of around 70% in a three-category scale (negative/neutral/positive) and 60% in a five-category scale (strongly negative/negative/neutral/positive/strongly positive). The first one was a comparison of the latency in the start time of the tool when setup with different servers, a Historian server and an MS SQL. bishop died 1555 the Bishop of Carlisle Robert Aldrich historian born 1954 Australian historian Robert Andrich born 1994 a German footballer new life for Years Since the Storm. This project investigates the forest-cover change during the period 1989-2005 in the region, with the combined use of remote-sensing satellite images, geographic information systems (GIS), and data-mining techniques. The results and findings from the analysis provide management with a better data driven approach and solution to make policies and decisions regarding the fate of the campaign/product. In addition, The Cluster-LASSO model surpasses the out of sample performance of LASSO model by 1.89%. The logistic regression model performed better than all the other models. The data in the database is entered by each project manager and relies on accurate and up-to-date entries. After fitting the logistic regression model, we will move to the tress approach for the model building. Because of the variation and uncertainty in demand, emergency-department staffing is particularly challenging. One base-case scenario models the current system while an alternative scenario re-directs non-critical patients to a local urgent-care center. In my capstone project, I plan to analyze 'Speed Dating Experiment’ dataset compiled and released by Columbia Business School Professors Ray Fisman and Sheena Iyengar for their paper “Gender Differences in Mate Selection: Evidence from a Speed Dating Experiment”. The final model was selected based on out of sample mean square error and assessed based on decision level prediction in the 2015 portfolio. Higher value of concordance, lower misclassification and higher AUC indicates the predicted model has good discriminatory power. With the use of all the recommendations Airbnb can improve their service which will lead to happy customers and thus, better business. With a baseline of around seven hours in the initial system, these two scenarios reduce an ED patient's average time in the radiology department to less than two hours. We can use the variables which turned out to be important factors effecting churn and use them to design actionable strategies to reduce the churn. This data was split randomly so that 75% was used for training and 25% for testing. Note that I have followed IBM SPSS Insurance Customer Retention and Growth Blueprint as the definitive guideline for this modeling exercise. Over the past five years, 33 different special events have been hosted. And, the second problem revolves around creating more time savings for the maintenance staff (who are the end customers). With the advent of the mobile operating systems (OS), Microsoft revamped its value offering and launched the Windows 10 OS in July 2015 that works across devices (Laptops, Desktops, Tablets and Mobile phones). Ole Jacobsen, NFL Decision Making: Evaluating Game Situations with a Markov Chain, July 24, 2014 (Michael Fry, David Rogers) From the distribution of this score, it was observed that the most of the active loan customers fall into low-risk category. This is mainly due to the fact that survival of the platform and revenue potential are dependent on the user experience levels. TalkingData is China’s largest independent big data service platform, covers over 70% of active mobile devices nationwide. One potential problem of binning is the information loss due to transformation. This automated solution allowed re-pricing to be done more frequently (monthly) which resulted in an annual incremental revenue of ~$500,000 for the payment processor. For the analysis cosine similarity is used to compute the similarity between users and items. Several scenarios such as increasing the number of CSRs and trunk lines are simulated to decrease the percent of customers who are thrown out of the contact center queue due to system overflow, while at the same time keeping a check on the total cost of the system. In certain states, the state government controls a portions of the three-tier system. to help the dealers make a decision. Sagar Vinaykumar Tupkar, Predicting Credit Card Defaults, July 2016, (Yichen Qin, Peng Wang) Preliminary review of Company A’s data indicates that the average monthly write downs for the Environmental Department is approximately $17,000. The model is trained over a calibration period of 9 months and the predictions are tested for a holdout period of 4 months. While removing the missing data, half of the information is lost and as a result the logistic regression model built gave poor results in prediction with AUC as 0.6 and misclassification rate as 0.54.
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