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The "Comprehensive Machine Learning Framework in R" is an all-inclusive toolkit for data preprocessing, WOE calculation, and model evaluation, designed for robust machine learning applications and equipped with cross-validation and extensibility features.
Functions for quantifying pollutant decay in rivers based on data obtained through Lagrangian sampling in reaches with high potential for interference from ungauged lateral inputs (e.g., discharges from combined sewer overflows in an urban river)
This Market Basket Analysis project in Python/R offers a versatile solution for uncovering purchasing patterns from transactional data. Utilizing powerful libraries like pandas, sqlalchemy, and mlxtend, it's ideal for businesses seeking to enhance marketing strategies and boost sales through data-driven insights.
Automate retail reporting emails in R using Outlook, sending daily/weekly reports to specified teams with attached files. Example emails and paths provided.
This R script fetches financial data, such as stock prices, using the Alpha Vantage API. It provides a simple way to retrieve the latest close price for a given stock symbol.
"Aggregated Mean Calculator" in R efficiently computes feature weights by grouping data and calculating mean values, essential for predictive analytics and statistical modeling. Ideal for insightful data analysis.
This R project conducts a comprehensive analysis of customer distances and sales for retail stores. Leveraging SQL server connectivity, it calculates distances, categorizes sales within specified radii, and outputs insightful data for retail business decision-making.