We used the decision tree regression model from the scikit-learn module (version 0.23.2) in Python 3.8 to train the decision trees. This model uses a modified version of the CART algorithm to find the ...

Clinical-ready AI tool boosts breast cancer detection via decision tree algorithms The system is structured around a client-server architecture designed to provide scalability, remote accessibility, ...

Overall, the combination of computer vision systems with the decision tree algorithm proved to be an effective method for tomato quality classification. Performance metrics including accuracy (0.836), ...

This article presents a novel methodology for estimating the double-cage model (DCM) for three-phase induction machines (TIMs) using decision tree-based algorithms. Validated on a diverse dataset of ...

Decision Tree (DT) regression, as a tree-structured regression model with one root node and several leaf nodes, is used to predict values. The prediction is made by recursively partitioning the input, ...

Using machine learning to improve prediction accuracy, this study investigates the use of the Extra Tree (Extremely Randomized Trees) algorithm for heart disease prediction. The research includes data ...

During the off-season Ward and his team made the decision to compete for the 2025 South Boston Speedway Sentara Health Late Model Stock Car Division title.

Figure 4. Histogram of bang lenth. 4.2. Decision Boundaries The decision tree model’s reliance on attribute 7 (e.g., Reach) reflects the effectiveness of the model in establishing clear decision ...

This article presents a demo of decision tree regression, implemented from scratch, using the C# language. The concepts underlying decision tree regression are relatively simple, but implementation is ...