Knowledge-Based Classification Algorithms Knowledge-Based Classification Algorithms Knowledge-based classification algorithms refer to a category of machine learning algorithms that employ pre-existing knowledge or rules to classify novel instances or data points. The algorithms in question are dependent on a knowledge base, which is a compilation of established patterns, rules, or associations among attributes, for the purpose of predicting outcomes or assigning class designations to unobserved data. In contrast to conventional classification algorithms that acquire patterns or rules directly from the training data, knowledge-based classification algorithms utilise pre-existing knowledge or domain expertise to steer the classification procedure. Pre-existing knowledge can be sourced from human experts or obtained from pre-existing resources such as databases, ontologies, or expe...
Wokeism, a term that gained prominence in the 2010s, refers to a heightened awareness of social, cultural, and political issues, with a particular focus on combating racism and promoting social justice. This concept has become a focal point of both praise and criticism, dividing public opinion along ideological lines. In this article, we explore the two sides of wokeism and delve into the complexities of this social phenomenon. The Positive Side: Wokeism has undoubtedly played a crucial role in raising awareness about systemic inequalities and injustices that have long plagued society. By alerting people to racial prejudice, discrimination, and other forms of social disparity, it has fostered a deeper understanding of marginalized communities' struggles. Many proponents argue that being woke is a step towards progress, as it encourages individuals to empathize, listen, and take meaningful action to address societal imbalances. One of the significant achievements of Wokeism is its a...