Hierarchical Estimation as Basis for Hierarchical Forecasting

Hierarchical Basis for Unstructured

Forecasting in Hierarchical Models

Risk Estimation for Hierarchical Classifier

We describe the Hierarchical Classifier (HC), which is a hybrid architecture [1] built with the help of supervised training and unsu-pervised problem clustering. We prove a theorem giving the estimationˆR of HC risk. The proof works because of an improved way of computing cluster weights, introduced in this paper. Experiments show thatˆR is correlated with HC real error. This allows us to usê R...

Choosing the Best Hierarchical Clustering Technique Based on Principal Components Analysis for Suspended Sediment Load Estimation

1- INTRODUCTION The assessment of watershed sediment load is necessary for controling soil erosion and reducing the potential of sediment production. Different estimates of sediment amounts along with the lack of long-term measurements limits the accessibility to reliable data series of erosion rate and sediment yield. Therefore, the observed data of suspended sediment load could be used to ...

Bridging the semantic gap for software effort estimation by hierarchical feature selection techniques

Software project management is one of the significant activates in the software development process. Software Development Effort Estimation (SDEE) is a challenging task in the software project management. SDEE is an old activity in computer industry from 1940s and has been reviewed several times. A SDEE model is appropriate if it provides the accuracy and confidence simultaneously before softwa...