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Found 8 papers, 3 papers with code
RollingLDA: An Update Algorithm of Latent Dirichlet Allocation to Construct Consistent Time Series from Textual Data
We propose a rolling version of the Latent Dirichlet Allocation, called RollingLDA.
Employing an Adjusted Stability Measure for Multi-Criteria Model Fitting on Data Sets with Similar Features
We propose the approach of tuning the hyperparameters of a predictive model in a multi-criteria fashion with respect to predictive accuracy and feature selection stability.
Adjusted Measures for Feature Selection Stability for Data Sets with Similar Features
For data sets with similar features, for example highly correlated features, most existing stability measures behave in an undesired way: They consider features that are almost identical but have different identifiers as different features.
Feature Selection Methods for Cost-Constrained Classification in Random Forests
Cost-sensitive feature selection describes a feature selection problem, where features raise individual costs for inclusion in a model.
Implications on Feature Detection when using the Benefit-Cost Ratio
In situations with large cost differences and small effect sizes, the BCR missed relevant features and preferred cheap noise features.
Improving Reliability of Latent Dirichlet Allocation by Assessing Its Stability Using Clustering Techniques on Replicated Runs
Based on the newly proposed measure for LDA stability, we propose a method to increase the reliability and hence to improve the reproducibility of empirical findings based on topic modeling.
High Dimensional Restrictive Federated Model Selection with multi-objective Bayesian Optimization over shifted distributions
To carry out a clinical research under this scenario, an analyst could train a machine learning model only on local data site, but it is still possible to execute a statistical query at a certain cost in the form of sending a machine learning model to some of the remote data sites and get the performance measures as feedback, maybe due to prediction being usually much cheaper.
Machine Learning meets Data-Driven Journalism: Boosting International Understanding and Transparency in News Coverage
Migration crisis, climate change or tax havens: Global challenges need global solutions.
