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DEPARTAMENTOS
INTERESSE GERAL
INTERESSE GERAL 2
LIVROS TÉCNICOS
LIVROS TÉCNICOS 2
CATEGORIAS
- IMPORTADOS
Discovery Science
Cód:
491_9783030615260
De: R$ 0,00Por: R$ 929,52ou X de
Classification.- Evaluating Decision Makers over Selectively Labelled Data: A Causal Modelling Approach.- Mitigating Discrimination in Clinical Machine Learning Decision Support using Algorithmic Processing Techniques.- WeakAL: Combining Active Learning and Weak Supervision.- Clustering.- Constrained Clustering via Post-Processing.- Deep Convolutional Embedding for Painting Clustering: Case Study on Picassos Artworks.- Dynamic Incremental Semi-Supervised Fuzzy Clustering for Bipolar Disorder Episode Prediction.- Iterative Multi-Mode Discretization: Applications to Co-Clustering.- Data and Knowledge Representation.- COVID-19 Therapy Target Discovery with Context-aware Literature Mining.- Semantic Annotation of Predictive Modelling Experiments.- Semantic Description of Data Mining Datasets: An Ontology-based Annotation Schema.- Data Streams.- FABBOO - Online Fairness-aware Learning under Class Imbalance.- FEAT: A Fairness-enhancing and Concept-adapting Decision Tree Classifer.- Unsupervised Concept Drift Detection using a Student{Teacher Approach.- Dimensionality Reduction and Feature Selection.- Assembled Feature Selection For Credit Scoring in Micro nance With Non-Traditional Features.- Learning Surrogates of a Radiative Transfer Model for the Sentinel 5P Satellite.- Nets versus Trees for Feature Ranking and Gene Network Inference.- Pathway Activity Score Learning Algorithm for Dimensionality Reduction of Gene Expression Data.- Machine learning for Modelling and Understanding in Earth Sciences.- Distributed Processing.- Balancing between Scalability and Accuracy in Time-Series Classification for Stream and Batch Settings.- DeCStor: A Framework for Privately and Securely Sharing Files Using a Public Blockchain.- Investigating Parallelization of MAML.- Ensembles.- Extreme Algorithm Selection with Dyadic Feature Representation.- Federated Ensemble Regression using Classification.- One-Class Ensembles for Rare Genomic Sequences Identification.- Explainable and Interpre
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