Publications by Souleymane Doumbia, Group Member: Fomba Kassoh
Presenation: Predicting House Sale Prices
Predicting House Sale Prices Souleymane Doumbia, Data 622 Final Project 2024-12-22 Introduction Predicting house prices is critical for real estate stakeholders. This project aims to build a predictive model to estimate house prices using property features. Dataset: House Prices: Advanced Regression Techniques. Problem Statement Objectives: D...
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Predicting House Sale Prices - Final Project D622
Introduction Accurately predicting house prices is essential for stakeholders in the real estate industry, including agents, developers, and homeowners. Reliable predictions help optimize pricing strategies, guide investment decisions, and provide insights into market trends. This project aims to develop a predictive model that identifies relations...
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Food Security and Nutrition in the U.S.
Food Security and Nutrition in the U.S. Souleymane Doumbia - Data 608 Story 6 2024-12-21 Introduction Addressing Food Security and Nutrition in the United States Food insecurity and malnutrition are not just global issues—they affect millions of Americans. This project focuses on: Examining food security data by age, gender, and state. Explo...
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Impact of Earth Temperature on Cyclonic Storms
Impact of Earth Temperature on Cyclonic Storms Souleymane Doumbia - Data 608 & Story 5 2024-12-18 I. Devastating Impact of Cyclonic Storms Cyclonic storms like hurricanes, typhoons, and tornadoes have caused catastrophic damage worldwide. Let’s explore their connection to rising Earth temperatures. II. Global Temperature Trends (1850-2024 ) ...
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A Comparative Analysis of Decision Trees and SVM Algorithms: Insights and Applications
Introduction Machine learning algorithms offer robust solutions for analyzing and understanding complex datasets. Among these algorithms: Decision Trees: Known for their simplicity and interpretability, they create models that are easy to understand and explain. Support Vector Machines (SVMs): Renowned for handling high-dimensional data and captur...
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Solving Problems 7.2 and 7.5 from Kuhn and Johnson
Introduction This document presents solutions to a series of exercises from Chapter 7 in the book Applied Predictive Modeling by Max Kuhn and Kjell Johnson. These exercises focus on non-linear regression techniques, including Neural Networks, Multivariate Adaptive Regression Splines (MARS), Support Vector Machines (SVM), and K-Nearest Neighbors (KN...
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Solving Problems 6.2 and 6.3 from Kuhn and Johnson
Introduction This document presents solutions to a series of exercises from Chapter 6 in the book Applied Predictive Modeling by Max Kuhn and Kjell Johnson. These exercises are designed to deepen understanding of predictive modeling techniques, including feature selection, model evaluation, and insights from predictive performance metrics. We will ...
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Using Decision Trees and Random Forests to Classify Countries by Maternal Mortality Risk
Introduction Title: Using Decision Trees and Random Forests to Classify Countries by Maternal Mortality Risk Maternal mortality is a critical global health issue, reflecting disparities in healthcare access and quality. The World Health Organization (WHO) defines maternal mortality ratios (MMR) as the number of maternal deaths per 100,000 live birt...
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Solving Problems 8.1, 8.2, 8.3, and 8.7 from Kuhn and Johnson
Introduction This document presents solutions to a series of exercises from Chapter 8 in the book Applied Predictive Modeling by Max Kuhn and Kjell Johnson. Each problem builds on the concepts of data preprocessing, model evaluation, and interpretation in predictive modeling. We will address the following problems one at a time: Problem 8.1: This ...
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Time Series Forecasting for ATM Cash Withdrawals and Power Usage
Introduction This project analyzes and forecasts time series data across two distinct domains: cash withdrawals at ATMs and residential power usage. The analysis is divided into two parts: Part A focuses on ATM cash withdrawals, exploring patterns and trends, applying multiple forecasting models, selecting the best-performing model, and exporting ...
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