Results 41 to 50 of about 305,651 (314)
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
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Konsep Decision Tree Reptree untuk Melakukan Optimasi Rule dalam Fuzzy Inference System Tsukamoto
Jurnal Teknologi Informasi dan Ilmu Komputer, 2022 Penelitian ini menjelaskan tentang decision tree REPTree dalam membuat suatu rule yang terbentuk dari produksi minyak kelapa sawit di PT Tapiana Nadenggan, yang dipengaruhi oleh faktor banyaknya kelapa sawit, permintaan yang ada, serta persediaan yang ...
Tundo Tundo, Shofwatul 'Uyun
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Jurnal Teknologi Informasi dan Ilmu Komputer, 2021 Penelitian ini menerangkan analisis decision tree J48, REPTree dan Random Tree dengan menggunakan metode fuzzy Tsukamoto dalam penentuan jumlah produksi minyak kelapa sawit di perusahaan PT Tapiana Nadenggan dengan tujuan untuk mengetahui decision tree ...
Tundo Tundo, Shofwatul 'Uyun
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Omnivariate decision trees [PDF]
IEEE Transactions on Neural Networks, 2001 Univariate decision trees at each decision node consider the value of only one feature leading to axis-aligned splits. In a linear multivariate decision tree, each decision node divides the input space into two with a hyperplane. In a nonlinear multivariate tree, a multilayer perceptron at each node divides the input space arbitrarily, at the expense ...
Olcay Taner Yildiz, Ethem Alpaydin
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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
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Pembentukan Model Pohon Keputusan pada Database Car Evaluation Menggunakan Statistik Chi-Square
Contemporary Mathematics and Applications (ConMathA), 2022 The study discusses problems related to the formation of a decision tree based on a collection of evaluation data records obtained from a number of car buyers. This secondary data was obtained from the UCL machine learning website.
Retno Maharesi
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CoRR, 2020 Decision trees (DTs) epitomize what have become to be known as interpretable machine learning (ML) models. This is informally motivated by paths in DTs being often much smaller than the total number of features. This paper shows that in some settings DTs can hardly be deemed interpretable, with paths in a DT being arbitrarily larger than a PI ...
Yacine Izza +2 more
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Fault Trees, Decision Trees, And Binary Decision Diagrams: A Systematic Comparison [PDF]
Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021), 2021 In reliability engineering, we need to understand system dependencies, cause-effect relations, identify critical components, and analyze how they trigger failures. Three prominent graph models commonly used for these purposes are fault trees (FTs), decision trees (DTs), and binary decision diagrams (BDDs). These models are popular because they are easy
Jimenez-Roa, L.A. +2 more
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An Ensemble-Based Decision Tree Approach for Educational Data Mining [PDF]
, 2018 Nowadays, data mining and machine learning techniques are applied to a variety of different topics (e. g., healthcare and disease, security, decision support, sentiment analysis, education, etc.).
Xujuan Zhou +5 more
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Investigating Evaluation Measures in Ant Colony Algorithms for Learning Decision Tree Classifiers [PDF]
, 2015 Ant-Tree-Miner is a decision tree induction algorithm that is based on the Ant Colony Optimization (ACO) meta- heuristic. Ant-Tree-Miner-M is a recently introduced extension of Ant-Tree-Miner that learns multi-tree classification models.
Otero, Fernando E.B. +5 more
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