Results 61 to 70 of about 726,930 (286)

Diverse Models, United Goal: A Comprehensive Survey of Ensemble Learning

CAAI Transactions on Intelligence Technology
Ensemble learning, a pivotal branch of machine learning, amalgamates multiple base models to enhance the overarching performance of predictive models, capitalising on the diversity and collective wisdom of the ensemble to surpass individual models and ...
Ziwei Fan, Zhiwen Yu, Kaixiang Yang, Wuxing Chen, Xiaoqing Liu, Guojie Li, Xianling Yang, C. L. Philip Chen   +7 more
doaj   +1 more source

Exploiting the Regularized Greedy Forest Algorithm Through Active Learning for Predicting Student Grades: A Case Study

Knowledge
Student performance prediction is a critical research challenge in the field of educational data mining. To address this issue, various machine learning methods have been employed with significant success, including instance-based algorithms, decision ...
Maria Tsiakmaki, Georgios Kostopoulos, Sotiris Kotsiantis   +2 more
doaj   +1 more source

Prognostic Impact of European LeukemiaNet Genetic Risk Stratification System in Adult Patients With Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
This study aimed to evaluate the prognostic value of ELN2017 in predicting survival outcomes and to assess the impact of clinical and molecular factors such as age, FLT3 and NPM1 mutations, and allogeneic hematopoietic stem cell transplantation (allo‐HSCT).
Mobina Shrestha, Bishwas Mandal, Vishal Mandal, Asis Shrestha, Amir Babu Shrestha   +4 more
wiley   +1 more source

Learning Nonlinear Functions Using Regularized Greedy Forest

, 2013
We consider the problem of learning a forest of nonlinear decision rules with general loss functions. The standard methods employ boosted decision trees such as Adaboost for exponential loss and Friedman's gradient boosting for general loss.
Johnson, Rie, Zhang, Tong
core   +2 more sources

Aging Is a Key Driver for Adult Acute Myeloid Leukemia

Aging and Cancer, EarlyView.
Acute myeloid leukemia (AML) is a classical age‐related hematologic malignancy, and a key driver of AML is aging, which profoundly regulates intrinsic factors such as genomic instability, epigenetic reprogramming, and metabolic dysregulation, and alters bone marrow microenvironment.
Rong Yin, Haojian Zhang
wiley   +1 more source

Comment: Boosting Algorithms: Regularization, Prediction and Model Fitting

, 2008
The authors are doing the readers of Statistical Science a true service with a well-written and up-to-date overview of boosting that originated with the seminal algorithms of Freund and Schapire. Equally, we are grateful for high-level software that will
Buja, Andreas, Mease, David, Wyner, Abraham J.   +2 more
core   +1 more source

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Explainable AI-based feature importance analysis for ovarian cancer classification with ensemble methods

Frontiers in Public Health
IntroductionOvarian Cancer (OC) is one of the leading causes of cancer deaths among women. Despite recent advances in the medical field, such as surgery, chemotherapy, and radiotherapy interventions, there are only marginal improvements in the diagnosis ...
Ashwini Kodipalli, Ashwini Kodipalli, V. Susheela Devi, Shyamala Guruvare, Taha Ismail   +4 more
doaj   +1 more source

Functional Connectivity Linked to Cognitive Recovery After Minor Stroke

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri, Isabella Dallasta, Ciaran Stone, Sophia Girgenti, Neda Gould, Rafael H. Llinas, Jonathan Z. Simon, Elisabeth Breese Marsh   +7 more
wiley   +1 more source

SelfieBoost: A Boosting Algorithm for Deep Learning [PDF]

, 2017
We describe and analyze a new boosting algorithm for deep learning called SelfieBoost. Unlike other boosting algorithms, like AdaBoost, which construct ensembles of classifiers, SelfieBoost boosts the accuracy of a single network.
Shalev-Shwartz, Shai
core