Results 1 to 10 of about 9,741 (54)

Comparative Analysis of Deterministic and Nondeterministic Decision Trees for Decision Tables from Closed Classes [PDF]

Entropy
In this paper, we consider classes of decision tables with many-valued decisions closed under operations of the removal of columns, the changing of decisions, the permutation of columns, and the duplication of columns.
Azimkhon Ostonov, Mikhail Moshkov
doaj   +2 more sources

On Complexity of Deterministic and Nondeterministic Decision Trees for Conventional Decision Tables from Closed Classes

Entropy, 2023
In this paper, we consider classes of conventional decision tables closed relative to the removal of attributes (columns) and changing decisions assigned to rows.
Azimkhon Ostonov, Mikhail Moshkov
doaj   +1 more source

Complexity of Deterministic and Strongly Nondeterministic Decision Trees for Decision Tables From Closed Classes

IEEE Access
This paper investigates classes of decision tables (DTs) with 0-1-decisions that are closed under the removal of attributes (columns) and changes to the assigned decisions to rows.
Azimkhon Ostonov, Mikhail Moshkov
doaj   +1 more source

Comparison of Complexity of Regular Versus Oblivious Decision Trees for Decision Tables With Many-Valued Decisions From Closed Classes

IEEE Access
In this work, we examine decision table (DTA) classes that are closed in terms of decision modification (i.e., the sets of decisions) and attribute deletion (i.e., columns).
Azimkhon Ostonov, Mikhail Moshkov
doaj   +1 more source

Lower Bounds on Cardinality of Reducts for Decision Tables from Closed Classes [PDF]

Annals of computer science and information systems
Azimkhon Ostonov, Mikhail Moshkov
doaj   +1 more source

NeuroFusionNet: a hybrid EEG feature fusion framework for accurate and explainable Alzheimer's Disease detection. [PDF]

Sci Rep
Akbar F, Alkhrijah Y, Usman SM, Khalid S, Ihsan I, Alawad MA.   +5 more
europepmc   +1 more source

EMDS-7-FSCIL: a benchmark for Few-Shot Class-Incremental Learning in environmental microorganism recognition. [PDF]

Front Microbiol
Zhou J, Zhang Y, Xu S, Hu Y, Zeng J, Yin Y.   +5 more
europepmc   +1 more source

Design of an in-pipe inspection robotic system (IPIRS) with YOLOv8-LSTM integration for real-time in-pipe navigation. [PDF]

Sci Rep
Elkholy H, Meligy R, Bassiuny AM, Mansour NA.   +3 more
europepmc   +1 more source

Flexible Bayesian Inference for Identifying Significantly Correlated Multiple Pathway Sets. [PDF]

Stat Med
Jin P, Yun Y, Kim I.
europepmc   +1 more source

Predicting dominant terrestrial biomes at a global scale using machine learning algorithms, climate variable indices, and extreme event indices. [PDF]

PLoS One
Sato H.
europepmc   +1 more source