Results 81 to 90 of about 6,176,379 (373)
Decision Tree Algorithm Considering Distances Between Classes
IEEE Access, 2022 Decision tree algorithm (DT) is a commonly used data mining method for classification and regression. DT repeatedly divides a dataset into pure subsets based on impurity measurements such as entropy and Gini.
Sangyong Lee +3 more
doaj +1 more source
Decision Stream: Cultivating Deep Decision Trees
, 2017 Various modifications of decision trees have been extensively used during the past years due to their high efficiency and interpretability. Tree node splitting based on relevant feature selection is a key step of decision tree learning, at the same time ...
Ignatov, Andrey, Ignatov, Dmitry
core +1 more source
FAHT: An Adaptive Fairness-aware Decision Tree Classifier [PDF]
International Joint Conference on Artificial Intelligence, 2019 Automated data-driven decision-making systems are ubiquitous across a wide spread of online as well as offline services. These systems, depend on sophisticated learning algorithms and available data, to optimize the service function for decision support ...
Wenbin Zhang, Eirini Ntoutsi
semanticscholar +1 more source
Molecular Oncology, EarlyView.This study explores salivary RNA for breast cancer (BC) diagnosis, prognosis, and follow‐up. High‐throughput RNA sequencing identified distinct salivary RNA signatures, including novel transcripts, that differentiate BC from healthy controls, characterize histological and molecular subtypes, and indicate lymph node involvement.
Nicholas Rajan +9 more
wiley +1 more source
Prediksi Rating Film IMDb Menggunakan Decision Tree
Jurnal Teknologi Informasi dan Ilmu Komputer, 2023 Industri Film bukan hanya industri atau pusat hiburan semata melainkan menjadi pusat bisnis global. Popularitas atau kesuksesan film box office selalu menjadi perhatian di seluruh dunia.
Rifqy Rosdiyah Ilmi +2 more
doaj +1 more source
GENESIM : genetic extraction of a single, interpretable model [PDF]
, 2016 Models obtained by decision tree induction techniques excel in being interpretable.However, they can be prone to overfitting, which results in a low predictive performance. Ensemble techniques are able to achieve a higher accuracy. However, this comes at
De Turck, Filip +4 more
core +2 more sources
A Novel Hyperparameter-Free Approach to Decision Tree Construction That Avoids Overfitting by Design [PDF]
IEEE Access, 2019 Decision trees are an extremely popular machine learning technique. Unfortunately, overfitting in decision trees still remains an open issue that sometimes prevents achieving good performance.
Rafael García Leiva +3 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.In this exploratory study, we investigated the relationship between the gut microbiota and outcome in patients with metastatic hormone receptor‐positive breast cancer, treated in a randomized clinical trial with chemotherapy alone or chemotherapy in combination with immune checkpoint blockade.
Andreas Ullern +7 more
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
Extremely Fast Decision Tree [PDF]
Knowledge Discovery and Data Mining, 2018 We introduce a novel incremental decision tree learning algorithm, Hoeffding Anytime Tree, that is statistically more efficient than the current state-of-the-art, Hoeffding Tree.
Chaitanya Manapragada +2 more
semanticscholar +1 more source