Sentence examples for create classifications from inspiring English sources

Psychologist Hans Eysenck was working with traumatised soldiers when he began to create classifications for different personality types.

The general awareness of the need to use such methods stems primarily from the initially narrower debate that took place within systematics in the 1960s and 1970s over how to create classifications of organisms that are "scientific" and as such, are transparent recipes that are accessible to others, instead of being "private" and non-scientific.

Users may create classifications and/or groupings of these countries for a particular analysis.

Several studies in the 1970s attempted to create classifications of people who self-harm [ 17, 18], but these efforts were not of great clinical value and were gradually abandoned.

And in an accompanying Observer article he defends the need to create classification systems for mental disorder.

The reason for the successful performance of the models on sequences of species not included in training, as seen for both Candida species and S. pombe is that SVMs gather sufficient information to create classification model based on only a small set of the training examples.

We used discriminant analysis to create classification functions that identified seven key lexical categories that predict expert scoring (interrater reliability with experts = 0.899).

In our analysis of student explanations to the question, we were able to use discriminant analysis based on expert raters to create classification functions that resulted in intraclass correlation coefficients of 0.749.

For every process step, the created classifications are analyzed.

Our interest in this paper is on the choice of spatial and categorical scale, and their interaction, in creating classifications of land cover from remotely sensed measurements.

To rule out that the statistical properties of our projection analysis methods are creating classifications out of random data sets, we carried out these methods on noisy data obtained through two shuffling procedures.