Pages that link to "Item:Q2665857"

The following pages link to Gamma mixture density networks and their application to modelling insurance claim amounts (Q2665857):

Displaying 8 items.

• A gamma kernel density estimation for insurance loss data (Q2015623) (← links)
• Deep quantile and deep composite triplet regression (Q2685516) (← links)
• Modelling claim number using a new mixture model: negative binomial gamma distribution (Q5222443) (← links)
• Micro-level prediction of outstanding claim counts based on novel mixture models and neural networks (Q6173881) (← links)
• The use of autoencoders for training neural networks with mixed categorical and numerical features (Q6174075) (← links)
• Method of Winsorized Moments for Robust Fitting of Truncated and Censored Lognormal Distributions (Q6549261) (← links)
• Machine learning with high-cardinality categorical features in actuarial applications (Q6556598) (← links)
• Leveraging Weather Dynamics in Insurance Claims Triage Using Deep Learning (Q6567876) (← links)