Recent years medical fields are facing more challenging issues while detecting disease
because day by day disease are developed due to the several factors. The IoT medical …

As the amount of data available exponentially grows, data scientists are aware that finding
the value in the data is key to a successful data exploiting. However, the data rarely presents …

Identifying mineralization zones is a critical component of quantifying the distribution of
target minerals using well-established mineral resource estimation techniques. Domains are …

In recent years, supervised machine learning methods have increased attention to extracting
clinically relevant information from complex health data. Ensemble learning methods enable …

The extensive implementation of machine learning (ML) has transformed data analysis and
decision-making processes. However, the process of choosing suitable ML algorithms for a …

In the modern era, the classification dilemma of Imbalanced Datasets (IDs) has received a
sustained interest, both in practical and theoretical aspects. One widely used Oversampling …

Preprocessing techniques can increase the predictive performance, or even allow the use,
of Machine Learning (ML) algorithms. This occurs because many of these techniques can …

Learning label noise is gaining increasing attention from a variety of disciplines, particularly
in supervised machine learning for classification tasks. The k nearest neighbors (k NN) …

An accurate occupancy detection is the inevitable part to save the energy consumption in an
office room or a building. Recently, a new approach which uses statistical machine learning …

Now-a-days most of the children faced tooth decay and acid erosion problem in their teeth
because of continuous bacterial infection, acid segregation, presents of food particles in …