Abstract
Web content increasing in every sector has become challenging task to find the useful information. Question Answering system in agriculture domain help farmers to provide the accurate answer. Farmer asking the queries relevant to pomegranate fruit in which question classification plays an important role for various questions asked by farmer to categorize or to identify the type of question Different question classification methods have been proposed to provide solutions for classification of question. In this research, we are considering the different pomegranate questions that can be asked by farmer to classify the questions correctly using different machine learning methods. A proposed framework for question classification having multiple classes i.e. name, descriptive, location, numeric and entity: other which enables machine learning algorithms to categorize the type of question. This paper compares various machine learning algorithms and result shows K-Nearest Neighbor, SVM & Decision tree performed well with good accuracy.
Recommended Citation
Niranjan, Prashant Y. and Rajpurohit, Vijay S.
(2024)
"Different Approaches for Multi-Class Classification using Machine Learning Techniques,"
American Journal of Science & Engineering (AJSE): Vol. 3:
Iss.
3, Article 5.
Available at:
https://research.smartsociety.org/ajse/vol3/iss3/5