This paper mainly deals with various classification algorithms namely, Bayes. NaiveBayes, Bayes. BayesNet, Bayes. NaiveBayesUpdatable, J48, Randomforest, and Multi Layer Perceptron. It analyzes the hepatitis patients from the UC Irvine machine learning repository. The results of the classification model are accuracy and time. Finally, it concludes that the Naive Bayes performance is better than...

BACKGROUND Improving maternal health and reducing maternal mortality rate are key concerns. One of the eight millennium development goals adopted at the millennium summit, was to improve maternal health in Ethiopia. This leads towards discovering the factors that hinder postnatal care visit in Ethiopia. METHODS In this research, knowledge discovery from data (KDD) was applied to identify the ...

background non-alcoholic fatty liver disease (nafld) is the most common form of liver disease in many parts of the world. objectives the aim of the present study was to identify the most important factors influencing nafld using a classification tree (ct) to predict the probability of nafld. patients and methods this cross-sectional study was conducted in kavar, a town in the south of fars prov...

In this paper, the authors propose a new technique for classification of seizures, non-seizures, and seizure-free EEG signals based on non-linear trajectories signals. The are decomposed using EMD to obtain intrinsic mode functions (IMFs). phase space these IMFs is then reconstructed novel higher-order dimensions (3D, 4D, 5D, 6D, 7D, 8D, 9D, 10D). existing techniques seizure detection have depl...

Nowadays, breast cancer is the most frequent among women. Early detection a critical issue that can be effectively achieved by machine learning (ML) techniques. Thus in this article, methods to improve accuracy of ML classification models for prognosis are investigated. Wrapper-based feature selection approach along with nature-inspired algorithms such as Particle Swarm Optimization, Genetic Se...

Support Vector Machines (SVM) is a state-of-the-art, powerful algorithm in machine learning which has strong regularization attributes. Regularization points to the model generalization to the new data. Therefore, SVM can be very efficient for spam detection. Although the experimental results represent that the performance of SVM is usually more than other algorithms, but its efficiency is decr...

Building the survivability prediction models is a challenging task because they provide an important approach to assessing risk and prognosis. In this paper, we investigated the performance of combining of the Bagging with several weak learners to build 5-accurate breast cancer survivability prediction models from the Srinagarind hospital database in Thailand. These models could assist medical ...

ABSTRACT: In this paper, sorting of two Iranian varieties of pistachio, “Akbari” (Ak) and “Kaleghouchi” (Ka), by the decision tree and fuzzy logic classifier is investigated. 240 Ak and 120 Ka pistachio nuts impacted to a stainless steel plate through a chute, and the acoustic signal of these impacts picked up using a microphone and saved on a computer via a sound card. Further analysis has bee...

Developments in information technology has enabled accumulation of large databases and most of the environmental, agricultural and medical databases consist of large quantity of real time observatory datasets of high dimension space. The curse to these high dimensional datasets is the spatial and computational requirements, which leads to ever growing necessity of attribute reduction techniques...