Applied SPSS for Data Forecasting of Flowers Species Name

SPSS is powerful to analyze data clustering and forecasting. This paper intends to support people who are interesting the species of flowers the benefits of data forecasting with applied SPSS. It showed the species value forecasting based on sepal length and sepal width. As SPSS's background algorithms, it showed the KNN algorithm for data clustering and data forecasting. It includes one sample data was downloaded from Google and was analyzed and viewed. It used IBM SPSS statistics version 23 and PYTHON version 3.7 Aung Cho | Aung Si Thu | Aye Mon Win "Applied SPSS for Data Forecasting of Flowers Species Name" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26665.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-miining/26665/applied-spss-for-data-forecasting-of-flowers-species-name/aung-cho