… thirty-year history of ML by elaborating on supervised learning, unsupervised learning,
reinforcement learning … We critically review the thirty-year history of ML. Depending on how we …

Although use of machine translation (MT) technologies by learners may seem like a
relatively new issue in foreign language (FL) education, researchers have been investigating …

… of publications during the last thirty years. Topic and network … detection and classification
by machine-learning strategies”, … the relevance of machine learning approaches to correctly …

… or AutoML is a term coined by the machine learning community to refer to methods that aim
… of machine learning systems and applications [33]. In the context of supervised learning, …

… Figure 1 illustrates our taxonomy of evaluation failures in machine learning. Our taxonomy
can serve as a resource for machine learning researchers and practitioners to check for …

… machine learning … machine learning approaches in order to find solution to problems. In
this paper, we focus on general review of machine learning including various machine learning …

… symbolic techniques to those based on Machine Learning approaches, especially those
based … Wide Web, and six apply machine learning techniques to a variety of legal applications. …

Background Accurately predicting the survival rate of breast cancer patients is a major issue
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …

… Deep learning represents a subcategory of machine learning that is focused … -learning-based
machine learning as classical machine learning (classical ML), whereas machine learning …

… The research and practice of information systems have progressed by leaps and bounds
due to the emergence of big data analytics and machine learning. The paper undertakes a …