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Model Selection

Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models.

Source: Kernel-based Information Criterion

Papers

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Showing 901–950 of 2050 papers

TitleStatusHype
Detection and Evaluation of Clusters within Sequential Data—0
Complexity Matters: Effective Dimensionality as a Measure for Adversarial Robustness—0
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets—0
How to select predictive models for causal inference?—0
How to Select Pre-Trained Code Models for Reuse? A Learning Perspective—0
Bayesian CART models for insurance claims frequency—0
Compressed particle methods for expensive models with application in Astronomy and Remote Sensing—0
hv-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)—0
Hybrid methodology based on Bayesian optimization and GA-PARSIMONY to search for parsimony models by combining hyperparameter optimization and feature selection—0
Compressive Nonparametric Graphical Model Selection For Time Series—0
Detecting Signs of Model Change with Continuous Model Selection Based on Descriptive Dimensionality—0
Detecting Nonlinear Causality in Multivariate Time Series with Sparse Additive Models—0
Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference—0
Bayesian Boosting for Linear Mixed Models—0
Interpretability in Linear Brain Decoding—0
Hyperparameter Importance of Quantum Neural Networks Across Small Datasets—0
A Local Information Criterion for Dynamical Systems—0
MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data—0
Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model—0
Hypothesis Testing in High-Dimensional Regression under the Gaussian Random Design Model: Asymptotic Theory—0
ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets—0
Bayesian Anomaly Detection and Classification—0
Identification of Physical Processes and Unknown Parameters of 3D Groundwater Contaminant Problems via Theory-guided U-net—0
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach—0
Identifying spatiotemporal dynamics of Ebola in Sierra Leone using virus genomes—0
Identifying Technical Debt and Its Types Across Diverse Software Projects Issues—0
Designing Interpretable ML System to Enhance Trust in Healthcare: A Systematic Review to Proposed Responsible Clinician-AI-Collaboration Framework—0
Impact of Loss Model Selection on Power Semiconductor Lifetime Prediction in Electric Vehicles—0
Impact of Missing Values in Machine Learning: A Comprehensive Analysis—0
Conformal Prediction with Upper and Lower Bound Models—0
ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion—0
Improvement of Identification Procedure Using Hybrid Cuckoo Search Algorithm for TurbineGovernor and Excitation System—0
Improving Bias Correction Standards by Quantifying its Effects on Treatment Outcomes—0
Improving Group Lasso for high-dimensional categorical data—0
Improving hotel room demand forecasting with a hybrid GA-SVR methodology based on skewed data transformation, feature selection and parsimony tuning—0
Improving Model Robustness Using Causal Knowledge—0
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations—0
Consistencies and inconsistencies between model selection and link prediction in networks—0
Consistent model selection in the spiked Wigner model via AIC-type criteria—0
Improving VTE Identification through Adaptive NLP Model Selection and Clinical Expert Rule-based Classifier from Radiology Reports—0
Consistent Nonparametric Different-Feature Selection via the Sparsest k-Subgraph Problem—0
Modeling flexible behavior with remapping-based hippocampal sequence learning—0
Inconsistency of cross-validation for structure learning in Gaussian graphical models—0
Consistent Relative Confidence and Label-Free Model Selection for Convolutional Neural Networks—0
Incremental Learning for Fully Unsupervised Word Segmentation Using Penalized Likelihood and Model Selection—0
Independent Mobility GPT (IDM-GPT): A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models—0
Contextual-Bandit Anomaly Detection for IoT Data in Distributed Hierarchical Edge Computing—0
A Unified Dynamic Approach to Sparse Model Selection—0
Individual Text Corpora Predict Openness, Interests, Knowledge and Level of Education—0
Designing Ecosystems of Intelligence from First Principles—0
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