Classification and determination of pH value: A decision tree learning approach

• المؤلفون الرئيسيون: Chioson, Francheska B., Munsayac, Francisco Emmanuel T., Luta, Raphael Benedict G., Baldovino, Renann G., Bugtai, Nilo T.
• التنسيق: text
• منشور في: Animo Repository 2019
• الموضوعات: Decision trees; Hydrogen-ion concentration—Measurement; Machine learning; Mechanical Engineering
• الوصول للمادة أونلاين: https://animorepository.dlsu.edu.ph/faculty_research/2698
• المؤسسة: De La Salle University

In chemistry, the potential of hydrogen (pH) level is the measure of the acidity or basicity among substances. Generally, this level is determined through the use of a type of indicator dipped into an aqueous solution. A standard pH scale is used to classify the liquid as either basic or acidic. In this paper, the decision tree (DT) learning was implemented using the classification and regression trees (CART) algorithm in classifying whether a substance is basic or acidic. The input data used in this study is the HSV (hue, saturation, value) color space with their corresponding pH level, ranging from 0 to 14. A total of 1,410 data samples were used in which 70% were assigned for training and 30% for testing. Results displayed a high accuracy of 95.3%. Thus, DT algorithm is an effective choice in classifying the pH level of a substance. © 2018 IEEE.