Breast cancer has become the primary reason of death in women in developed countries. Breast cancer is the second most common cause of cancer death in women worldwide. The high incidence of breast cancer in women has increased significantly during the last few decades. In this paper we have discussed various data mining approaches that have been utilized for early detection of breast cancer. Br...

In the past, the plants have been studied for various reasons whether it is for medicine or diseases classification. A plant can be classified on the basis of its flowers, size and shape of the leaves including color, barks etc. The role of leaves in taxonomic classification of plants is very essential. This paper studies the effect of leaf image quality improvement by sharpening and enhancing ...

In these days WEKA has become one of the most important data mining and machine learning tools. Despite the fact that it incorporates many algorithms, on the classification area there are still some unimplemented features. In this paper we cover some of the missing features that may be useful to researchers and developers when working with decision tree classifiers. The rest of the paper presen...

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to b...

The present study has proposed three novel hybrid models by integrating traditional ensemble models, such as random forest, logitboost, and naive bayes, six newly developed of rotation forest (RF), decision tree (RF-DT), J48 (DF-J48), bayes (RF-NBT), neural network (RF-NN), M5P (RF-M5P) REPTree (RF-REPTree), with statistical i.e. weight evidence, logistic regression combination WOE LR. To predi...

In these days WEKA has become one of the most important data mining and machine learning tools. Despite the fact that it incorporates many algorithms, on the classification area there are still some unimplemented features. In this paper we cover some of the missing features that may be useful to researchers and developers when working with decision tree classifiers. The rest of the paper presen...

This research aimed on prediction of customer loyalty (Non loyal or Loyal) using the application of data mining in microfinance that helps to build a classification model which supports during loan decision making in the organization. In this study a classification model is built based on the loan data obtained from Joshua Multi Purpose Limited Liability Cooperative (JMPLLC). Experiments using ...

Precise rainfall forecasting is a common challenge across the globe in meteorological predictions. As rainfall forecasting involves rather complex dynamic parameters, an increasing demand for novel approaches to improve the forecasting accuracy has heightened. Recently, Rough Set Theory (RST) has attracted a wide variety of scientific applications and is extensively adopted in decision support ...

Machine learning is the study of computer algorithms that improve automatically with experience. In other words it is the ability of the computer program to acquire or develop new knowledge or skills from examples for optimising the performance of a computer or a mobile device. In this paper we apply machine learning techniques Bayes network, Logistic Regression, Decision Stump, J48, Random For...

The postures of wheelchair users can reveal their sitting habit, mood, and even predict health risks such as pressure ulcers or lower back pain. Mining the hidden information of the postures can reveal their wellness and general health conditions. In this paper, a cushion-based posture recognition system is used to process pressure sensor signals for the detection of user's posture in the wheel...