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...

Gait-based classification has gained much interest as a possible authentication method because it incorporate an intrinsic personal signature that is difficult to mimic. The study investigates machine learning techniques to mitigate the natural variations in gait among different subjects. We incorporated several machine learning algorithms into this study using the data mining package called Wa...

Calibration is often overlooked in machine-learning problem-solving approaches, even in situations where an accurate estimation of predicted probabilities, and not only a discrimination between classes, is critical for decision-making. One of the reasons is the lack of readily available open-source software packages which can easily calculate calibration metrics. In order to provide one such to...

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Clustering is a procedure to organizing the objects in to groups or clustered together, based on the principle of maximizing the intra-class similarity and minimizing the inter class similarity. The various clustering algorithms are analyzed and compare the performance of cluster...

The drug discovery and development process is lengthy and expensive, and bringing a drug to market may take up to 18 years and may cost up to 2 billion $US. The extensive use of computer-assisted drug design techniques may considerably increase the chances of finding valuable drug candidates, thus decreasing the drug discovery time and costs. The most important computational approach is represe...

Data mining became a popular research field these days. The reasons that attracted attention in information technology, the discovery of meaningful information from large collections of data. Data mining is the perception that we are data rich but very much information poor. Large amount of data is available all around but we can hardly able to turn them in to useful information. The comparativ...

This work aims to use sentiment analysis techniques, data mining, text mining and natural language processing to indicate the polarity of texts using SVM (support vector machine). Weka software and a movie review database from IMDb (internet movie database) were used. This work uses preprocessing filters and WRAPPER techniques and SVM for classification. It presents better results when compared...

There has been an emerging open source data mining software development in current times. In this work I carry out an empirical study to compare the performances of open source and commercial data mining software. The results clearly reveals that before and after data preprocessing of the two NASA datasets used in this work, commercial data mining software (MATLAB) outperforms open source data ...

This paper presents a tool for web usage mining. The aim is centered on providing a tool that facilitates the mining process rather than implement elaborated algorithms and techniques. The tool covers different phases of the CRISP-DM methodology as data preparation, data selection, modeling and evaluation. The algorithms used in the modeling phase are those implemented in the Weka project. The ...