Results 21 to 30 of about 320,698 (271)
Collapsing the Decision Tree: the Concurrent Data Predictor [PDF]
, 2021 A family of concurrent data predictors is derived from the decision tree classifier by removing the limitation of sequentially evaluating attributes. By evaluating attributes concurrently, the decision tree collapses into a flat structure. Experiments indicate improvements of the prediction accuracy.
arxiv +1 more source
Privacy-preserving decision tree for epistasis detection
Cybersecurity, 2019 The interaction between gene loci, namely epistasis, is a widespread biological genetic phenomenon. In genome-wide association studies(GWAS), epistasis detection of complex diseases is a major challenge. Although many approaches using statistics, machine
Qingfeng Chen, Xu Zhang, Ruchang Zhang
doaj +1 more source
Frontiers in Oncology, 2022 BackgroundThe aim of this study was to derive and validate a decision tree model to predict disease-specific survival after curative resection for primary cholangiocarcinoma (CCA).MethodTwenty-one clinical characteristics were collected from 482 patients
Bing Quan +17 more
doaj +1 more source
dtControl: Decision Tree Learning Algorithms for Controller Representation [PDF]
, 2020 Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent provably-correct controllers concisely. Compared to representations using lookup tables or binary decision diagrams, decision trees are smaller and more explainable.
arxiv +1 more source
Decision Support System Improving the Interpretability of Generated Tree-Based Models
Acta Electrotechnica et Informatica, 2022 A decision tree represents one of the most used data analysis methods for classification tasks. The generated decision models can be visualized as a graph, but this visualization is quite complicated for a domain expert to understand in large or ...
Klimonová Diana +3 more
doaj +1 more source
Implementasi Algoritma Ant Tree Miner Untuk Klasifikasi Jenis Fauna
Infotekmesin: Media Komunikasi Ilmiah Politeknik Cilacap, 2021 Classification is a field of data mining that has many methods, one of them is decision tree. Decision tree is proven to be able to classify many kinds of data such as image data and time series data.
Yunita Ardilla +2 more
doaj +1 more source
Tree in Tree: from Decision Trees to Decision Graphs [PDF]
arXiv, 2021 Decision trees have been widely used as classifiers in many machine learning applications thanks to their lightweight and interpretable decision process. This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional decision tree to a more generic and powerful directed acyclic graph.
arxiv
Data‐driven performance metrics for neural network learning
International Journal of Adaptive Control and Signal Processing, EarlyView., 2023 Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri +2 more
wiley +1 more source
Comprehensive decision tree models in bioinformatics.
PLoS ONE, 2012 PurposeClassification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of
Gregor Stiglic +3 more
doaj +1 more source
Decision tree-based Design Defects Detection
IEEE Access, 2021 Design defects affect project quality and hinder development and maintenance. Consequently, experts need to minimize these defects in software systems. A promising approach is to apply the concepts of refactoring at higher level of abstraction based on ...
Mohamed Maddeh +3 more
doaj +1 more source