Handling Non Communicable Disease Using Predictive Analysis of Data Mining Techniques

Abstract: Non communicable diseases (NCDs), though not as dangerous as communicable diseases as far as proliferation is concerned, these are dangerous by themselves because of their root causes. In this article, our main focus is on predictive analysis of smoking, which is a non-communicable disease, using regression analysis. Regression analysis is a cornerstone of predictive […]

Comparative Analysis of Pure and Hybrid Machine Learning Algorithms for Risk Prediction of Diabetes Mellitus

Abstract Diabetes, a chronic disease, occurs due to abnormal levels of glucose and insulin in our bodies. The major factors leading to the disease are lifestyle factors such as diet, insufficient physical activity, increased stress levels and obesity. One of the major issue with diabetes is the mildness of its symptoms which delays its diagnosis […]

USING LARGE SCALE DEEP LEARNING METHOD TO PREDICT PUNCTUATIONS IN TELUGU LANGUAGE

Abstract Punctuation performs an important role in language processing. However, automated speech recognization systems only output plain terms sequences. It really is then appealing to predict punctuations on simple word sequences. Earlier works are focused on using lexical features or prosodic cues captured from small corpus to predictable simple punctuations. When compared with simple punctuations, […]

Semantic Similarity based Web Document Clustering Using Hybrid Swarm Intelligence and FuzzyC-Means

Abstract   Information retrieval technology has been central to the success of the web. The volume of information stored and accessed on web is increasing continuously. This enlargement leads to the difficulties such as seeking and managing the existing information. The use of keyword based method in information retrieval processing is the reason behind this […]

Mining Sequential Patterns using Two-Tail Time Effect

Abstract The temporal component of the spatio-temporal databases is the key factor that leads to large accumulation of data. It can be said that continuous collection of spatial data, leads to spatio-temporal databases. An event type sequence is called as a sequential pattern and extracting such sequential patterns from spatio-temporal event data sets paves way […]