Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer ...

Artificial intelligence is rapidly changing the job market, automating jobs across industries. Therefore, in such a scenario, upskilling oneself in industry-relevant AI skills becomes even more ...

Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...

Abstract: In this paper, we propose an in-node microprocessor-based vehicle classification approach to analyze and determine the types of vehicles passing over a 3-axis magnetometer sensor. Our ...

Choosing the right algorithm for machine learning can make a huge difference in making your model very effective. Of many algorithms, two popular choices have been Decision Trees and Random Forests ...

Currently, the second most devastating form of cancer in people, particularly in women, is Breast Cancer (BC). In the healthcare industry, Machine Learning (ML) is commonly employed in fatal disease ...