In machine learning, two approaches outperform traditional algorithms: ensemble learning
and deep learning. The former refers to methods that integrate multiple base models in the …

Context Ensemble methods consist of combining more than one single technique to solve
the same task. This approach was designed to overcome the weaknesses of single …

Carcinoma is a primary source of morbidity in women globally, with metastatic disease
accounting for most deaths. Its early discovery and diagnosis may significantly increase the …

This research studies a support vector machine (SVM)-based ensemble learning algorithm
for breast cancer diagnosis. Illness diagnosis plays a critical role in designating treatment …

Topic extraction is an essential task in bibliometric data analysis, data mining and
knowledge discovery, which seeks to identify significant topics from text collections. The …

Typically performed by supervised machine learning algorithms, sentiment analysis is highly
useful for extracting subjective information from text documents online. Most approaches that …

The utilisation of DM (Data Mining) and ML (Machine Learning) approaches in the BC
(Breast Cancer) diagnosis has recently gained a lot of consideration. However, most of …

Breast cancer is a neoplastic disease which seriously threatens women's health. It is regard
as the most common cause of cancer death in women. Accurate detection and effective …

The use of machine learning (ML) and data mining algorithms in the diagnosis of breast
cancer (BC) has recently received a lot of attention. The majority of these efforts, however …

With the help of machine learning (ML) techniques, the possible errors made by the
pathologists and physicians, such as those caused by inexperience, fatigue, stress and so …