Results 71 to 80 of about 962,663 (328)
A logic boosting approach to inducing multiclass alternating decision trees [PDF]
, 2002 The alternating decision tree (ADTree) is a successful classification technique that combine decision trees with the predictive accuracy of boosting into a ser to interpretable classification rules.
Frank, Eibe +4 more
core +1 more source
Comparative study of adenosine 3′‐pyrophosphokinase domains of MuF polymorphic toxins
FEBS Open Bio, EarlyView.With the ultimate goal of understanding the association of toxin‐immunity modules to temperate phages, we characterized toxins from three prophages and examined cross‐protection from immunity proteins. The toxins exhibit adenosine 3′‐pyrophosphokinase activity and are toxic in Escherichia coli.
Eloïse M. Paulet +6 more
wiley +1 more source
Machine Learning: Science and Technology, 2023 Deep learning systems, especially in critical fields like medicine, suffer from a significant drawback, their black box nature, which lacks mechanisms for explaining or interpreting their decisions.
Jose Sigut +4 more
doaj +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2023 We develop the first fully dynamic algorithm that maintains a decision tree over an arbitrary sequence of insertions and deletions of labeled examples. Given ε>0 our algorithm guarantees that, at every point in time, every node of the decision tree uses a split with Gini gain within an additive ε of the optimum.
Bressan M., Damay G., Sozio M.
openaire +2 more sources
ANALYZING BIG DATA WITH DECISION TREES [PDF]
, 2014 ANALYZING BIG DATA WITH DECISION ...
Leong, Lok Kei
core +1 more source
Protein O‐glycosylation in the Bacteroidota phylum
FEBS Open Bio, EarlyView.Species of the Bacteroidota phylum exhibit a unique O‐glycosylation system. It modifies noncytoplasmic proteins on a specific amino acid motif with a shared glycan core but a species‐specific outer glycan. A locus of multiple glycosyltransferases responsible for the synthesis of the outer glycan has been identified.
Lonneke Hoffmanns +2 more
wiley +1 more source
Decision Trees for Uncertain Data [PDF]
2009 IEEE 25th International Conference on Data Engineering, 2009 Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/quantization errors, data staleness, and multiple repeated ...
Tsang, S +4 more
openaire +5 more sources
A PANoptosis‐Based Signature for Survival and Immune Predication in Glioblastoma Multiforme
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective PANoptosis is a concept of total cell death characterized by pyroptosis, apoptosis, and necroptosis. We aimed to explore the clinical significance of PANoptosis‐related genes (PARGs) in glioblastoma multiforme (GBM). Methods Expression profiles of GBM were downloaded from the XENA database as a training dataset to construct a ...
Jun Yang +4 more
wiley +1 more source
Succinct Explanations With Cascading Decision Trees [PDF]
arXiv, 2020 The decision tree is one of the most popular and classical machine learning models from the 1980s. However, in many practical applications, decision trees tend to generate decision paths with excessive depth. Long decision paths often cause overfitting problems, and make models difficult to interpret.
arxiv