NIP - An Imperfection Processor to Data Mining datasets

NIP - An Imperfection Processor to Data Mining datasets

Every day there are more techniques that can work with low quality data. As a result, issues related to data quality have become more crucial and have consumed a majority of the time and budget of data mining projects. One problem for researchers is the lack of low quality data in order to test their techniques with this data type. Also, as far as we know, there is no software tool focused on t...

Data Mining for Imbalanced Datasets: An Overview

A dataset is imbalanced if the classification categories are not approximately equally represented. Recent years brought increased interest in applying machine learning techniques to difficult "real-world" problems, many of which are characterized by imbalanced data. Additionally the distribution of the testing data may differ from that of the training data, and the true misclassification costs...

Visualization & Data Mining for High Dimensional Datasets

Measuring Data Quality of Geoscience Datasets Using Data Mining Techniques

Currently there are many methods of collecting geoscience data, such as station observations, satellite images, sensor networks, etc. All of these data sources from different regions and time intervals are combined in geoscience research activities today. Using a mixture of several different data sources may have benefits but may also lead to severe data quality problems, such as inconsistent d...

An Optimal Model for Medicine Preparation Using Data Mining

Introduction: Lack of financial resources and liquidity are the main problems of hospitals. Pharmacies are one of the sectors that affect the turnover of hospitals and due to lack of forecast for the use and supply of medicines, at the end of the year, encounter over-inventory, large volumes of expired medicines, and sometimes shortage of medicines. Therefore, medicine prediction using availabl...