Results 61 to 70 of about 4,043,886 (303)
IEEE Transactions on Knowledge and Data Engineering, 2017 Uncovering causal relationships in data is a major objective of data analytics. Causal relationships are normally discovered with designed experiments, e.g. randomised controlled trials, which, however are expensive or infeasible to be conducted in many cases.
Jiuyong Li +4 more
openaire +3 more sources
Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
Engineering and Applied Science Research, 2022 Decision Trees are a common approach used for classifying unseen data into defined classes. The Information Gain is usually applied as splitting criteria in the node selection process for constructing the decision tree.
Sirichanya Chanmee, Kraisak Kesorn
doaj
Molecular Oncology, EarlyView.Tumour heterogeneity and clonal evolution of metastatic salivary gland cancer were evaluated in two patients with adenoid carcinoma and one patient with myoepithelial carcinoma. Radiology‐guided autopsy enabled multi‐region sampling (total samples n = 149), followed by whole‐genome sequencing and phylogenetic reconstruction (17 tumour samples, 4–7 per ...
Gerben Lassche +10 more
wiley +1 more source
A Chi-MIC Based Adaptive Multi-Branch Decision Tree
IEEE Access, 2021 Since the decision trees (DTs) have an advantage over “black-box” models, such as neural nets or support vector machines, in terms of comprehensibility, such that it might merit improvement for further optimization.
Jiahao Ye +6 more
doaj +1 more source
Molecular Oncology, EarlyView.Taxanes are widely used chemotherapeutics whose effects on cellular mechanics remain poorly understood. We show that paclitaxel induces rapid cellular contraction by promoting GEF‐H1 dissociation from microtubules and non‐muscle myosin II activation through RhoA/ROCK.
Gloria Asensio‐Juárez +5 more
wiley +1 more source
MAPTree: Beating “Optimal” Decision Trees with Bayesian Decision Trees
Proceedings of the AAAI Conference on Artificial IntelligenceDecision trees remain one of the most popular machine learning models today, largely due to their out-of-the-box performance and interpretability. In this work, we present a Bayesian approach to decision tree induction via maximum a posteriori inference of a posterior distribution over trees.
Colin Sullivan +2 more
openaire +4 more sources
Bivariate decision trees [PDF]
, 1997 Decision tree methods constitute an important and much used technique for classification problems. When such trees are used in a Datamining and Knowledge Discovery context, ease of interpretation of the resulting trees is an important requirement to be met.
Bioch, JC (Cor) +2 more
openaire +3 more sources
Growing Toward the Future: The Rowan Tree Church: Our 16th Annual Report, Hallows 1997-Hallows 1998. [PDF]
, 1997 This digital asset was created from the original digital scans by Rev. Paul V. Beyerl and provided to the Valdosta State University, Archives & Special Collections to be part of their Rowan Tree Church Periodicals Collection of the New Age Movements ...
Rowan Tree Church
core
FEBS Open Bio, EarlyView.The dFoCC pipeline starts with observed DED and resting‐state coordinates, which are then used to generate a library of triggered states. Correlation analysis of the calculated DED features of each candidate vs observed DED permits quantitative evaluation of candidate structural quality.
Meng Iao Fong +3 more
wiley +1 more source