Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple indicators. Three machine learning methods are compared for this task: decision ...

The aim of this paper is to develop a rapid, and highly sensitive quantitative HPLC fingerprint method with multiple indicators by using the Compound Chinese Medicine Wuwei Changyanning granule and 5 herbs in the prescription. The quantitative fingerprint chromatogram with multiple indicators was investigated. ⅰ)6 compositions included rutin, gallic acid, chlorogenic acid, atractylenolideⅠ, pac...

The aim of this paper is to develop a rapid, and highly sensitive quantitative HPLC fingerprint method with multiple indicators by using the Compound Chinese Medicine Wuwei Changyanning granule and 5 herbs in the prescription. The quantitative fingerprint chromatogram with multiple indicators was investigated. ⅰ)6 compositions included rutin, gallic acid, chlorogenic acid, atractylenolideⅠ, pac...

In the social and other sciences many data are collected with a known but complex underlying structure. Over the past two decades there has been an increase in the use of multilevel modelling techniques that account for nested data structures. Often however the underlying data structures are more complex and cannot be fitted into a nested structure. First, there are cross-classified models wher...

Factor models are widely used in summarizing large datasets with few underlying latent factors and in building time series forecasting models for economic variables. In these models, the reduction of the predictors and the modeling and forecasting of the response y are carried out in two separate and independent phases. We introduce a potentially more attractive alternative, Sufficient Dimensio...