Machine Learning Techniques to Web-Based Intelligent Learning Diagnosis System

Abstract

In this paper, machine learning techniques to web-based intelligent learning diagnosis system are implemented. The main intent of this paper is to cultivate the ability of learner’s knowledge. This is done by integrating number of opportunities to the learner. This method helps the learner to improve knowledge and ability to work on diagnosis system. Diagnosis system will predict the results in very effective way. Initially, input data is mapped based on features using data sample mapping procedure. Next, the mapped data is classified using optimal classification technique. The optimal classification technique is based on the features. This classification techniques is performs its operation in two ways they are testing and training. The tested and trained data extracts its features using feature extracted method. Both SVM and ELM will classify the data based on extraction. At last, data is evaluated and classified. From results, it can observe that accuracy, reliability, precision, recall, F1 score, and mean gives effective outcome compared with Naïve Bayesian classifier.