Market Basket Analysis and Association Rule Mining
Market Basket Analysis helps merchants to boost their business. It is a kind of Machine Learning namely Association Rule Mining in a data set for all transactions that consists of items bought in the store by several customers over a period of time. A seller will use these findings to change, or update, or add items in inventory, he also may use them to change the layout of the physical store or rather an online store. The picture presents some results of Market Basket Analysis. First, the data set was converted into transaction data so that all items that are bought together in one invoice are in one row. Then, a special algorithm were used to mine frequent item sets and association rules. The algorithm employs level-wise search for frequent item sets. The calculations were passed with a parameter set that had to return all the rules that have a support of at least 0.1% and confidence of at least 40%. The rules sorted by decreasing confidence are probable market baskets.
About Me
Coherent professional with a problem-solving mentality accompanied by many years of researching and teaching experience in Ukrainian universities. With superior quality in data modeling and simulation, I am confident my work will exceed expectations [login to view URL] Specializing in: - Projects pertaining to Statistical/Data Analysis, Machine Learning, Mathematics, and Physics. - Open AI machine learning and natural language processing (NLP) techniques to analyze documents and respond user queries in a chatbot. - Consulting Businesses through Financial/Inventory/Customer Data Analysis and Forecast. Skills that pertain to this project are the following: - Excellent Communicator - Problem-solver - Attention to detail - Analytical Thinker Analysis Skills: - Multivariate Statistical Analysis - Regression Analysis - Factor Analysis & Sensitivity Analysis - Bayesian Analysis - Monte Carlo Analysis - Experimental Designs - Time Series Analysis - Forecasting - Statistical Quality Control - Spatial Data Analysis - Structural Equation Modeling. Program Proficiency: - Python - R programming - Rapidminer - Matlab - Microsoft Excel. I do not outsource my work; I am a one-man team. Mostly available from 9:00 to 19:00 GMT+2
