In this work, we propose a novel K-ary splitting method for regression trees and incorporate it into the regression forest framework. Unlike standard binary splitting, where the splitting rule is selected from a predefined set of binary splitting rules via trial-and-error, the proposed K-ary splitting method first finds clusters of the training data which at least locally minimize the empirical...

Label noise in training data can significantly degrade a model’s generalization performance for supervised learning tasks. Here we focus on the problem that noisy labels are primarily caused by mislabeled confusing samples, which tend to be concentrated near decision boundaries rather than uniformly distributed, and whose features should equivocal. To address problem, propose an ensemble method...

a subsurface drainage network mainly carries unsteady flow and data are not usually available for model parameters calibration in such networks. in the present research, the finite volume method using the time splitting scheme was employed to develop a computer code for solving the one dimensional unsteady flow equations. using corrugated sub drainage pipes, an experimental prototype setup was ...

This paper addresses compound splitting for Dutch in the context of broadcast news transcription. Language models were created using original text versions and text versions that were decomposed using a data-driven compound splitting algorithm. Language model performances were compared in terms of outof-vocabulary rates and word error rates in a real-world broadcast news transcription task. It ...

This paper addresses compound splitting for Dutch in the context of broadcast news transcription. Language models were created using original text versions and text versions that were decomposed using a data-driven compound splitting algorithm. Language model performances were compared in terms of outof-vocabulary rates and word error rates in a real-world broadcast news transcription task. It ...

let $pounds$ be the category of all locally compact abelian (lca) groups‎. ‎in this paper‎, ‎the groups $g$ in $pounds$ are determined such that every extension $0to xto yto gto 0$ with divisible‎, ‎$sigma-$compact $x$ in $pounds$ splits‎. ‎we also determine the discrete or compactly generated lca groups $h$ such that every pure extension $0to hto yto xto 0$ splits for each divisible group $x$ ...

In this work, we propose a novel node splitting method for regression trees and incorporate it into the regression forest framework. Unlike traditional binary splitting, where the splitting rule is selected from a predefined set of binary splitting rules via trial-and-error, the proposed node splitting method first finds clusters of the training data which at least locally minimize the empirica...

Abstract For several decades, shear-wave splitting (SWS) parameters (fast polarization orientations and splitting times) have been widely measured to reveal the orientation and strength of mantle anisotropy. One of the most popularly used techniques for obtaining station-averaged SWS parameters is the multiple-event stacking technique (MES). Results from previous studies suggest the splitting t...

We introduce a novel algorithm for the efficient detection and tracking of features in spatiotemporal atmospheric data, as well as for the precise localization of the occurring genesis, lysis, merging and splitting events. The algorithm works on data given on a four-dimensional structured grid. Feature selection and clustering are based on adjustable local and global criteria, feature tracking ...