Design and Develop Data Analysis and Forecasting of the Sales Using Machine Learning

被引:1
|
作者
Kadam, Vinod [1 ]
Vhatkar, Sangeeta [1 ]
机构
[1] Thakur Coll Engn & Technol, Mumbai 400101, Maharashtra, India
关键词
Time series; RFM model; Market basket analysis; Apriori algorithm; ARIMA; SARIMA;
D O I
10.1007/978-981-16-4863-2_14
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data Analysis and Forecasting on Supermarket Sales Transactions is a proposed system which focus on the betterment of the sales in the business. The whole proposed system comprises mostly of 4 sections: Exploratory Data Analysis in experiences, exploratory data assessment is an approach to manage separating enlightening assortments to gather their standard ascribes, routinely with visual strategies. Exploratory Data Analysis proposes the fundamental strategy for performing starting evaluations on information to find plans, to spot anomalies, to test theory and to check questions with the help of framework estimations and graphical portrayals. Client Segmentation Theoretically we will have fragments like Low Value: Customers who are less dynamic than others, not continuous purchaser/guest and creates extremely low-zero-ossibly negative income. Mid Value: trying to everything. Of-ten utilizing our foundation (however not however much our High Values), genuinely continuous and creates moderate income. High Value: The gathering we would prefer not to lose. High Revenue, Frequency and low Inactivity. Market Basket Analysis is a technique which recognizes the nature of connection between sets of things purchased together and perceive instances of co-occasion. A co-event is when at least two things occur together. Time-arrangement techniques for forecasting. Determining is a methodology or a framework for assessing future pieces of a business or the movement. It is a technique for deciphering past data or experience into evaluations of what might be on the horizon..
引用
收藏
页码:157 / 171
页数:15
相关论文
共 50 条
  • [31] Improving Short-term Output Power Forecasting Using Topological Data Analysis and Machine Learning
    Senekane, Makhamisa
    Matjelo, Naleli Jubert
    Taele, Benedict Molibeli
    INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND ENERGY TECHNOLOGIES (ICECET 2021), 2021, : 475 - 480
  • [32] Forecasting & Severity Analysis of COVID-19 Using Machine Learning Approach with Advanced Data Visualization
    Sarkar, Ovi
    Ahamed, Md Faysal
    Chowdhury, Pallab
    2020 23RD INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY (ICCIT 2020), 2020,
  • [33] Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data
    Gupta, Rangan
    Karmakar, Sayar
    Pierdzioch, Christian
    COMPUTATIONAL ECONOMICS, 2024, 64 (01) : 487 - 513
  • [34] Applying Machine Learning and Statistical Forecasting Methods for Enhancing Pharmaceutical Sales Predictions
    Fourkiotis, Konstantinos P.
    Tsadiras, Athanasios
    FORECASTING, 2024, 6 (01): : 170 - 186
  • [35] Exploratory Data analysis and sales forecasting of bigmart dataset using supervised and ANN algorithms
    Thivakaran T.K.
    Ramesh M.
    Measurement: Sensors, 2022, 23
  • [36] Electric Car Market Analysis Using Open Data: Sales, Volatility Assessment, and Forecasting
    Pelegov, Dmitry V. V.
    Chanaron, Jean-Jacques
    SUSTAINABILITY, 2023, 15 (01)
  • [37] Sales forecasting by combining clustering and machine-learning techniques for computer retailing
    Chen, I-Fei
    Lu, Chi-Jie
    NEURAL COMPUTING & APPLICATIONS, 2017, 28 (09): : 2633 - 2647
  • [38] Sales forecasting by combining clustering and machine-learning techniques for computer retailing
    I-Fei Chen
    Chi-Jie Lu
    Neural Computing and Applications, 2017, 28 : 2633 - 2647
  • [39] Using machine learning and big data for efficient forecasting of hotel booking cancellations
    Sanchez-Medina, Agustin J.
    C-Sanchez, Eleazar
    INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT, 2020, 89
  • [40] Time-Series Forecasting of Seasonal Data Using Machine Learning Methods
    Kramar, Vadim
    Alchakov, Vasiliy
    ALGORITHMS, 2023, 16 (05)