Gradient boosting survival tree with applications in credit scoring

Phone duration modeling using gradient tree boosting

Extracting Baseline Electricity Usage with Gradient Tree Boosting

To understand how specific interventions affect a process observed over time, we need to control for the other factors that influence outcomes. Such a model that captures all factors other than the one of interest is generally known as a baseline. In our study of how different pricing schemes affect residential electricity consumption, the baseline would need to capture the impact of outdoor te...

Credit scoring with macroeconomic variables using survival analysis

Survival analysis can be applied to build models for time of default on debt. In this paper we report an application of survival analysis to model default on a large data set of credit card accounts. We show that survival analysis is competitive for prediction of default in comparison with logistic regression. We explore the hypothesis that probability of default is affected by general conditio...

Collective Entity Disambiguation with Structured Gradient Tree Boosting

We present a gradient-tree-boosting-based structured learning model for jointly disambiguating named entities in a document. Gradient tree boosting is a widely used machine learning algorithm that underlies many topperforming natural language processing systems. Surprisingly, most works limit the use of gradient tree boosting as a tool for regular classification or regression problems, despite ...

Using DEA for Classification in Credit Scoring

Credit scoring is a kind of binary classification problem that contains important information for manager to make a decision in particularly in banking authorities. Obtained scores provide a practical credit decision for a loan officer to classify clients to reject or accept for payment loan. For this sake, in this paper a data envelopment analysis- discriminant analysis (DEA-DA) approach is us...