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Extracting meaningful pattern from data can be challenging. Irrelevant, redundant, noisy and unreliable data, misinterpretation of results and incompatibility of a technique to extract unknown patterns from data may lead analyst to develop an erroneous classifier. This research is encouraged by ‘No Free Lunch’ theorem that can be simplified as no classification technique that works best for every...
Air pollutants are really a hazardous problem in Bangladesh. This paper works on the relationship between the pollutants and the admittance of patients in the medical facilities and analyzes the reason behind the increase of the disease rate in the hospitals. The research collected medical data from the medical center named National Institute of Disease of the Chest and Hospital (NIDCH) that is located...
Data Mining is the process of finding pattern or useful information from large volume of data. The goal of this paper is to find the reason behind the unusual high birth rate by applying data mining techniques, e.g., decision tree, neural network, Bayes Classifier, Ripper and Support Vector Machine. The datasets were collected from the baseline survey conducted by the maternal neonatal and child health...
Rapid development of information technologies, in particular, progress in methods of collection, storage and processing of data has allowed to collect huge data arrays with the purpose of their analysis in many organizations. Opportunities of experts are not enough because amount of these data are too much. This generates demand for methods of automatic data analysis number of which annually increase...
Cardiovascular disease (CVD) is a big reason of morbidity and mortality in the current living style. Identification of Cardiovascular disease is an important but a complex task that needs to be performed very minutely, efficiently and the correct automation would be very desirable. Every human being can not be equally skillful and so as doctors. All doctors cannot be equally skilled in every sub specialty...
Data mining is now one of the most active field of research. Extracting those nuggets of information is becoming crucial and one of its important technique is classification. It helps to group the data in some predefined classes. Various techniques for classification exists which classifies the data using different algorithms. Each algorithm has its own area of best and worst performance. This paper...
Classification is an important data mining task, and decision trees have emerged as a popular classifier due to their simplicity and relatively low computational complexity. Time required to build a decision tree becomes intractable, as datasets get extremely large. To overcome this problem we proposed a parallel mode of ID3 algorithm. Decision tree building is well-suited for thread-level parallelism...
Heart failure comes in the top causes of death worldwide. The number of deaths from heart failure exceeds the number of deaths resulting from any other causes. Recent studies have focused on the use of machine learning techniques to develop predictive models that are able to predict the incidence of heart failure. The majority of these studies have used a binary output class, in which the prediction...
In recent years with the rapid growth of e-commerce and the large amounts of data collected through operational transactions, data mining techniques are becoming more useful to discover and understand unknown customer patterns. In the past, data mining has been used to find out which products are related in terms of having high sales and also ascertain which customers deserve credit facilities. There...
Diabetes mellitus is caused due to the increased level of sugar content in the blood. This can cause series complications like kidney failure, stroke, cancer, heart disease and blindness. The early detection and diagnosis, helps to identify and avoid these complications. A number of computerized information systems were designed using different classifiers for predicting and diagnosing diabetes. Selecting...
In this world, for any kind of information, people depend on internet. They use search engines like Google to search information over internet. The queries that are written on the web must be accurate which would give the relevant information related to user's Health Care. But there is huge amount of information on the internet and so it's difficult to get the relevant information easily. In case...
Decision tree technologists have been examined to be a helpful way to find out the human decision making within a host. Decision tree performs variable screening or feature selection. It requires relatively lesser effort from the users for the preparation of the data. In the proposed algorithm firstly we have undertaken to minimize the unnecessary redundancy in the decision tree, reducing the volume...
From a large amount of data, significant knowledge is discovered by means of applying techniques in the knowledge management process and those techniques is known as Data mining techniques. For a specific domain, a form of knowledge discovery called data mining is necessary for solving the problems. The classes of unknown data are detected by the technique called classification. Neural networks, rule...
Lupus is autoimmune heterogeneous disease and also a multi system disorder which predominantly affects women. There is no specific diagnostic test to predict Lupus and the diagnosis remains a clinical one, depends on a combination of clinical and laboratory features. Data mining is the use of sophisticated data analysis tools to discover previously unknown, hidden, valid patterns and relationships...
In real world as dependence on World Wide Web applications increasing day by day they transformed vulnerable to security attacks. Out of all the different attacks the SQL Injection Attacks are the most common. In this paper we propose SQL injection vulnerability prevention by decision tree classification technique. The proposed model make use famous decision tree classification model to prevent the...
The aim of this study is to compares some classification techniques used to predict the performance of student. It is helps to analyse the slow leaner in the semester exams that are likely study in poor which are used to improve their skill as early to achieve the goal in end semester. The task can be processed based on the several attributes to predict the performance of the student activity respectively...
Intrusion Detection System have been successful to prevent attacks on network resources, but the problem is that they are not adaptable in cases where new attacks are made i.e. they need human intervention for investigating new attacks. This paper proposes the creation of predictive intrusion detection model that is based on usage of classification techniques such as decision tree and Bayesian techniques...
Prediction is a challenging task and that too for weather is even more complex, dynamic and mind-boggling. Weather prediction poses right from the ancient times as a big herculean task, because it depends on various parameters to predict the dependent variables like temperature, rainfall, humidity, wind speed and direction, which are changing from time to time and weather calculation varies with the...
Every year many women die of breast cancer and the saddest part is that most of them die due to late diagnosis. A number of studies have been carried out to explore the basic reasons of breast cancer. Unfortunately, most of them failed to detect the main causes and the disease itself at a primary stage. On the other hand, it has already been proved that early detection of cancer can give the patient...
Data mining approaches have been used in business purposes since its inception; however, at present it is used successfully in new and emerging areas like education systems. Government of Bangladesh emphasizes the need to improve the education system. In this research, we use data mining approaches to predict students' final outcome, i.e., final grade in a particular course by overcoming the problem...
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