Gene expression information from microarray experiments is a primary form of data for biological analysis and can offer insights into disease processes and cellular behaviour. Suc...
In this paper, we study the problem of constructing private classifiers using decision trees, within the framework of differential privacy. We first construct privacy-preserving ID...
Probabilistic (or randomized) decision trees can be used to compute Boolean functions. We consider two types of probabilistic decision trees - one has a certain probability to give...
Laura Mancinska, Maris Ozols, Ilze Dzelme-Berzina,...
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...