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Decision Tree
This chapter first introduces the basic concept of the decision tree, then introduces feature selection, tree-generation and tree-pruning through ID3...
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Decision Tree
The decision tree is an important algorithm in machine learning. They mimic human thinking while making decisions and thus usually are easy to...
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Adapting video-based programming instruction: An empirical study using a decision tree learning model
The COVID-19 pandemic has forced a significant increase in the utilization of video-based e-learning platforms for programming education. These...
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Decision Tree
Decision tree is one of the simplest, yet popular, machine learning algorithms. It has a very long history of research and application, and has many...
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An improved decision tree algorithm based on boundary mixed attribute dependency
As an effective extension of rough set theory, the variable precision neighborhood rough set model has been applied to the attribute dependency-based...
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REBDT: A regular expression boundary-based decision tree model for Chinese logistics address segmentation
Chinese logistics address segmentation is a specific domain of the address resolution, which is very challenging due to language, culture, user...
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An efficient computer-aided diagnosis model for classifying melanoma cancer using fuzzy-ID3-pvalue decision tree algorithm
Visual observation and dermoscopic analysis are the most common methods of diagnosing skin cancer. In advanced stages, melanomas spread faster and...
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On the Decision Tree Complexity of Threshold Functions
In this paper we study decision tree models with various types of queries. For a given function it is usually not hard to determine the complexity in...
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Evaluation of Human-Understandability of Global Model Explanations Using Decision Tree
In explainable artificial intelligence (XAI) research, the predominant focus has been on interpreting models for experts and practitioners. Model...
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Evaluating trustworthiness of decision tree learning algorithms based on equivalence checking
Learning algorithms and their implementations are used as black-boxes to produce decision trees, e.g., for realizing critical classification tasks. A...
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Decision tree boosted varying coefficient models
Varying coefficient models are a flexible extension of generic parametric models whose coefficients are functions of a set of effect-modifying...
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Cautious Decision-Making for Tree Ensembles
Cautious classifiers are designed to make indeterminate decisions when the uncertainty on the input data or the model output is too high, so as to...
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Adversarially Robust Decision Tree Relabeling
Decision trees are popular models for their interpretation properties and their success in ensemble models for structured data. However, common...
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Big data decision tree for continuous-valued attributes based on unbalanced cut points
The decision tree is a widely used decision support model, which can quickly mine effective decision rules based on the dataset. The decision tree...
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Networked Industrial Control Device Asset Identification Method Based on Improved Decision Tree
Industrial control device asset identification is essential to the active defense and situational awareness system for industrial control network...
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Packet loss concealment method based on hidden Markov model and decision tree for AMR-WB codec
Packet loss concealment (PLC) techniques are utilized to improve the quality of Voice over IP (VoIP) communications by reconstructing missing speech...
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Entropy-Based Logic Explanations of Differentiable Decision Tree
Explainable reinforcement learning has evolved rapidly over the years because transparency of the model’s decision-making process is crucial in some...
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Differential Private (Random) Decision Tree Without Adding Noise
The decision tree is a typical algorithm in machine learning and has multiple expanded variations. However, regarding privacy, few in the variations...
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Next-generation cyber attack prediction for IoT systems: leveraging multi-class SVM and optimized CHAID decision tree
Billions of gadgets are already online, making the IoT an essential aspect of daily life. However, the interconnected nature of IoT devices also...
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Cost-Sensitive Decision Tree Induction on Dirty Data
As the rapid growth of data in our society, dirty data are increasingly common. In the process of cost-sensitive decision tree induction, dirty data...