Results 71 to 80 of about 741,105 (343)

Learning Optimal Decision Trees with SAT [PDF]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Explanations of machine learning (ML) predictions are of fundamental importance in different settings. Moreover, explanations should be succinct, to enable easy understanding by humans.  Decision trees represent an often used approach for developing explainable ML models, motivated by the natural mapping between decision tree paths and rules.
Nina Narodytska, Alexey Ignatiev, Filipe Pereira, Joao Marques-Silva   +3 more
openaire   +1 more source

Exploring Patients’ Profiles Associated With the Resolution of Acute Calcium Pyrophosphate Arthritis Treated With Colchicine and Prednisone: Post Hoc Analysis of a Randomized Controlled Trial

Arthritis Care &Research, EarlyView.
Objective The objective was to identify factors determining acute arthritis resolution and safety with colchicine and prednisone in acute calcium pyrophosphate (CPP) crystal arthritis. Methods We conducted a post hoc analysis of the COLCHICORT trial, which compared colchicine and prednisone for the treatment of acute CPP crystal arthritis, using a ...
Tristan Pascart, Laurène Norberciak, Pascal Richette, Pierre Robinet, Aurore Pacaud, Gauthier Marchasson, Thibault Rabin, Hélène Luraschi, Pierre Maciejasz, Anne‐France Georgel, Augustin Latourte, Hang‐Korng Ea, Sébastien Ottaviani, Charlotte Jauffret, Vincent Ducoulombier   +14 more
wiley   +1 more source

Thyroid Disease Prediction Using Machine Learning Model: Decision Tree

EDRAAK
Thyroid illness must be correctly classified in order to have an accurate diagnosis and effective therapy. Diagnostic accuracy and efficiency have both been found to improve with the use of machine learning methods.
Hadeel Alkhazzar, Bassam Moslem
doaj   +1 more source

Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning [PDF]

, 2014
A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and
Kurbatsky, Victor, Leahy, Paul, Sidorov, Denis, Spiryaev, Vadim, Tomin, Nikita, Zhukov, Alexei   +5 more
core   +2 more sources

Flux‐Regulated Crystallization of Perovskites Using Machine Learning‐Predicted Solvent Evaporation Rates for X‐Ray Detectors

Advanced Functional Materials, EarlyView.
By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto, Sergey Dayneko, Antoine Pavesic Junior, Nicholas Sandor, Alexander Hart, Yuki Haruta, Magdalena Bazalova‐Carter, Marcos J. L. Santos, Makhsud I. Saidaminov   +8 more
wiley   +1 more source

Research on Customer Churn Prediction Using Machine Learning Models [PDF]

SHS Web of Conferences
The percentage of consumers or subscribers that discontinue using a product or service within a given time frame is known as the “churn rate.” Hence, using machine learning models to estimate the number of possible churn consumers is crucial for ...
Jia Xiaolei
doaj   +1 more source

Forgetting Exceptions is Harmful in Language Learning [PDF]

, 1998
We show that in language learning, contrary to received wisdom, keeping exceptional training instances in memory can be beneficial for generalization accuracy.
Bosch, Antal van den, Daelemans, Walter, Zavrel, Jakub   +2 more
core   +5 more sources

Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production

Advanced Functional Materials, EarlyView.
Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen, Asier Agrelo‐Lestón, Ignasi Burgués‐Ceballos, Jordi Llorca, Lluís Soler   +4 more
wiley   +1 more source

Аргументи „за” и „против” държавната намеса в аграрния сектор

Икономика и управление на селското стопанство, 2012
Целта на настоящата статия е да представи някои от основните аргументи в подкрепа или против субсидирането на аграрния сектор. Анализът ще изложи накратко ролята на държавното подпомагане за земеделието според икономическата теория.
СТАНИМИР АНДОНОВ
doaj  

Active Learning Embedded in Incremental Decision Trees

, 2020
As technology evolves and electronic devices become widespread, the amount of data produced in the form of stream increases in enormous proportions. Data streams are an online source of data, meaning that it keeps producing data continuously. This creates the need for fast and reliable methods to analyse and extract information from these sources ...
Vinicius Eiji Martins, Victor G. Turrisi da Costa, Sylvio Barbon Junior   +2 more
openaire   +2 more sources