Precision, Recall, and F1-score are metrics that are often used to evaluate model
performance. Precision and Recall are very important to consider when the data is …

In recent years, with the rise of exceptional cloud computing technologies, machine learning
approach in solving complex problems has been greatly accelerated. In the field of text …

Imbalanced datasets are datasets with one or more underrepresented classes when
compared to other classes. Such datasets pose problems during classification due to the …

Imbalanced binary classification is a common problem in many real-world applications and
reduces the performance of machine learning algorithms in classifying minority class …

Aim: The study's goal is to carry out text classification analysis. Materials and Methods:
Accuracy is analyzed for text classification. It helps to organize the data entry data. The …

Data from sources like twitter, organizations internal communications, Face book, blogs are
keys in providing user the choice and scrutiny in organizational elevating. Text classification …

To combat the Covid-19 epidemic, the government issues laws governing vaccination
implementation. Health Minister Number Ten of 2021 issued the regulation. This program …

The increasing numbers of on-line text documents make the process of searching and
accessing documents related to a specific category a very difficult task. By classifying the …

Due to the recent escalation in the amount of text data available and used online, text
classification has become a staple for data analysts when extracting relevant information …

Textual data suffers from two main problems, large number of features and class imbalance.
Many conventional approaches and their variants exist in literature to solve both these …