It is an era of Internet of Things, where various types of sensors, especially wireless, are
widely used to collect huge amount of data to feed various systems such as surveillance …

Nowadays, there is an increasing demand in mining interesting patterns from the big data.
The process of analyzing such a huge amount of data is really computationally complex task …

The existing Dixon's test (DT) under classical statistics has been widely applied in a variety
of fields. The main target of DT is to recognize the outlier or suspicious observation in the …

Detecting outliers is an important step in data mining. Outliers not only hamper data quality
but also affect the output in case of prediction models. Prediction tools like Neural Networks …

Diabetes is one of the world's most common chronic disease. Prediabetes is the pre-phase
of diabetes, which slowly lead to type-2 diabetes. Early detection of diabetes prevents …

Power consumption is a major factor to be taken into consideration when using mobile
devices in the IoT field. Good Power management requires proper understanding of the way …

Education is a collective intelligence system where a group of persons ranging from
students to management thinks and work together to achieve institutions' goals. The primary …

Mining in data is an important step for knowledge discovery, which leads to extract new
patterns from datasets. It is a widespread methodology that has the capability to help …

In the era of big data, ensuring the quality of datasets has become increasingly crucial
across various domains. We propose a comprehensive framework designed to automatically …

La minería de datos anómalos es un área de la minería de datos que aborda el problema
de la detección de datos raros o comportamientos inusuales en los datos. Esta disciplina …