In this paper, we investigate the performance and success rates of Naïve Bayes Classification Algorithm for automatic classification of Turkish news into predetermined categories like economy, life, health etc. We use Apache Big Data technologies such as Hadoop, HDFS, Spark and Mahout, and apply these distributed technologies to Machine Learning. Keywords—news classification, distributed machin...

Retinal blood vessels are affected by a variety of eye diseases, including hypertensive retinopathy (HR) and diabetic (DR). A person with HR needs to be sure check their eyes regularly, which requires the use computer vision methods analyze images back help ophthalmologists automatically. Automated diagnostic systems useful for diagnosing different retinal diseases patients who need establish a...

Naïve Bayes (NB) is an efficient and effective classifier in many cases. However, NB might suffer from poor performance when its conditional independence assumption is violated. While most recent research focuses on improving NB by alleviating the conditional independence assumption, we propose a new Meta learning technique to scale up NB by assuming an altered strategy to the traditional Casca...

Automatic text classification into predefined categories is an increasingly important task given the vast number of electronic documents available on the Internet and enterprise servers. Successful text classification relies heavily on the vital task of dimensionality reduction, which aims to improve classification accuracy, give greater expression to the classification process, and improve cla...

Classification using naive bayes algorithm for air quality dataset has an accuracy rate of 39.97%. This result is considered not good and by all existing data attributes. By doing pre-processing, namely feature selection the gain ratio algorithm, Naive Bayes increases to 61.76%. proves that can improve performance classification. dataset. While Water Quality 93.18%. These results are 95.73%. Ba...

This paper presents a comparative case study on the classification accuracy between 5 methods for golf putting performance analysis. In a previous work, a digital camera was used to capture 30 trials of 6 expert golf players. The detection of the horizontal position of the golf club was performed using a computer vision technique followed by the estimation algorithm Darwinian Particle Swarm Opt...

Lung diseases are the disorders that affect the lungs, the organs that allow us to breathe and it is the most common medical conditions worldwide especially in India. The diseases such as pleural effusion and normal lung are detected and classified in this work. The purpose of the work is to detect and classify the lung diseases by effective feature extraction through moment invariants, feature...

In this paper, we propose a semantic naïve Bayes classifier (SNBC) to improve the conventional naïve Bayes classifier (NBC) by incorporating “document-level” semantic information for document classification (DC). To capture the semantic information from each document, we develop semantic feature extraction and modeling algorithms. For semantic feature extraction, we first apply a log-Bilinear d...

In recent years, the remarkableexpansion of web technologies, lead to an massive quantity of user generated information in online systems.This large amount of information on web platforms make them viable for use as data sources, in applications based on opinion mining and sentiment analysis.Sentiment analysishas become a vital part in today’s era. Post massiveexpansion of web technology, revie...