Search Results for author:
Found 7 papers, 5 papers with code
Combining Predictions under Uncertainty: The Case of Random Decision Trees
A common approach to aggregate classification estimates in an ensemble of decision trees is to either use voting or to average the probabilities for each class.
Tree-Based Dynamic Classifier Chains
However, the method requires a fixed, static order of the labels.
Correlation-based Discovery of Disease Patterns for Syndromic Surveillance
Early outbreak detection is a key aspect in the containment of infectious diseases, as it enables the identification and isolation of infected individuals before the disease can spread to a larger population.
Revisiting Non-Specific Syndromic Surveillance
Infectious disease surveillance is of great importance for the prevention of major outbreaks.
DeepDB: Learn from Data, not from Queries!
The typical approach for learned DBMS components is to capture the behavior by running a representative set of queries and use the observations to train a machine learning model.
Databases
Improving Outbreak Detection with Stacking of Statistical Surveillance Methods
Our results on synthetic data show that it is challenging to improve the performance with a trainable fusion method based on machine learning.
Model-based Approximate Query Processing
However, classical AQP approaches suffer from various problems that limit the applicability to support the ad-hoc exploration of a new data set: (1) Classical AQP approaches that perform online sampling can support ad-hoc exploration queries but yield low quality if executed over rare subpopulations.
