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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 1526–1550 of 2050 papers

TitleStatusHype
An Overview of Human Activity Recognition Using Wearable Sensors: Healthcare and Artificial Intelligence—0
An Unsupervised Anomaly Detection in Electricity Consumption Using Reinforcement Learning and Time Series Forest Based Framework—0
A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection—0
A Powerful Subvector Anderson Rubin Test in Linear Instrumental Variables Regression with Conditional Heteroskedasticity—0
Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock—0
Approximate Leave-one-out Cross Validation for Regression with _1 Regularizers (extended version)—0
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework—0
Approximation of Intractable Likelihood Functions in Systems Biology via Normalizing Flows—0
A Practitioner's Guide to Automatic Kernel Search for Gaussian Processes in Battery Applications—0
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study—0
Area under the ROC Curve has the Most Consistent Evaluation for Binary Classification—0
A Regret-Variance Trade-Off in Online Learning—0
A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods—0
A Review of Change of Variable Formulas for Generative Modeling—0
A Review of Cross-Sectional Matrix Exponential Spatial Models—0
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning—0
Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities—0
Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor—0
A Rule-Based Epidemiological Modelling Framework—0
A Sentiment Analysis of Medical Text Based on Deep Learning—0
A simple application of FIC to model selection—0
A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model—0
A spectral clustering-type algorithm for the consistent estimation of the Hurst distribution in moderately high dimensions—0
On The Stability of Interpretable Models—0
AssistedDS: Benchmarking How External Domain Knowledge Assists LLMs in Automated Data Science—0
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