Classification is one of the important tasks in data mining and machine learning.
Classification performance depends on many factors as well as data characteristics. Some …

The presence of lead in drinking water creates a public health crisis, as lead causes
neurological damage at low levels of exposure. The objective of this research is to explore …

Lead is a chemical contaminant that threatens public health, and high levels of lead have
been identified in drinking water at locations across the globe. Under-served populations …

Medical record instances can have missing values which makes them unsuitable for
learning process. Data Imputation is normally done to fill one or more missing data attribute …

Predicting the outcome of National Basketball Association (NBA) matches poses a
challenging problem of interest to the research community as well as the general public. In …

In recent years, imbalanced dataset classification has received significant attention due to its
application in real-world problems, resulting in emergence of a new class of algorithms …

Discretization is an important preprocessing technique, especially in classification problems.
It reduces and simplifies data, accelerates the learning process, and improves learner …

Imputation of missing data values is an important pre-processing task for mining of medical
data records. Application of data mining principles, techniques requires the dataset to be …

Continuous live weight monitoring can be used to identify optimum marketing weight,
production or health problems. In this research we repurposed specialized automatic scales …

Mining medical datasets is a challenging problem before data mining researchers as these
datasets have several hidden challenges compared to conventional datasets. Starting from …