Background: Gastric cancer is the fifth most common cancer and the third top cause of cancer related death with about 1 million new cases and 700,000 deaths in 2012. The aim of this investigation was to identify important factors for outcome using a random survival forest (RSF) approach. Materials and Methods: Data were collected from 128 gastric cancer patients through a historical cohort stud...

Random forests are a very effective and commonly used statistical method, but their full theoretical analysis is still an open problem. As a first step, simplified models such as purely random forests have been introduced, in order to shed light on the good performance of random forests. In this paper, we study the approximation error (the bias) of some purely random forest models in a regressi...

In our previous two installments on innovativeness we provided overviews of how forest industry managers define “innovative” companies and what they see as primary hurdles to innovativeness. Here we cover the remaining findings regarding how managers might measure innovativeness and what they do to proactively increase innovativeness within their firms. Findings in this area may be particularly...

We combine random forest (RF) and conditional random field (CRF) into a new computational framework, called random forest random field (RF). Inference of (RF) uses the Swendsen-Wang cut algorithm, characterized by MetropolisHastings jumps. A jump from one state to another depends on the ratio of the proposal distributions, and on the ratio of the posterior distributions of the two states. Prior...

Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise, does not overfit and offers possibilities for explanation and visualization of its output. We investigate some possibilities to increase strength or decrease correlation of individual trees in the forest. Using sever...

It is shown that many properties of Lyα forest absorbers can be derived using simple physical arguments. Analytical expressions are derived for the density and the size of an absorber as a function of its neutral hydrogen column density, which agree well with both observations and hydrodynamical simulations. An expression is presented to compute ΩIGM from the observed column density distributio...

Forest fires are one of the most important factors that threaten the ecological balance in the countries that are affected by the Mediterranean climate such as Turkey. Forests, that constitute 1⁄4 of the total area of our country, are in great danger of fire, especially during summer period. In 74,294 forest fires, we lost 1,630,000 hectares of forest area since 1937. This area is three times l...

We investigated local forest management practices in Osaka, Japan aiming to clarify mechanisms that hinder long-term, sustainable forestry operation by carrying out forest surveys and interview surveys. Because mountain districts in Japan now face declining and aging populations, forestry work has shifted to forest owners’ associations, with efficient forest management being required on an ad h...

Forest aboveground biomass (AGB) was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat), Moderate Resolution Imaging Spectro-radiometer (MODIS) imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic charac...

The most popular approach for analyzing survival data is the Cox regression model. The Cox model may, however, be misspecified, and its proportionality assumption is not always fulfilled. An alternative approach is random forests for survival outcomes. The standard split criterion for random survival forests is the log-rank test statistics, which favors splitting variables with many possible sp...