Sentence examples for assess classification from inspiring English sources

Next, we present a summary of the meta-data and geometrical measures we use to assess classification difficulty.

The most common and typical method used in the present study is to assess classification accuracy with the help of error matrix (Congalton 1991).

In this paper we are particularly interested in examining the use of cross-validation to select and assess classification and regression models.

A set of experiments was carried out to gather m-D signatures of personnel targets undertaking different action and typical feature extraction algorithms and classifier were used to assess classification performance.

We implemented an over-sampling framework (i.e., recorded an excessive amount of information) with two observers to 1) identify a sampling intensity that balanced precision with our resource constraints, and 2) assess classification and detection of squirrel burrows and ant nests across vegetation conditions.

Effectively this procedure builds a classification model with 90% of the spectra and then tests the remaining 10% to assess classification accuracy.

We address the problem of selecting and assessing classification and regression models using cross-validation.

The following migraine features were assessed: classification; attack frequency, intensity, disability, and duration; family history; and medications used.

Methodological advances in the last decade or so have shown that certain common methods of selecting and assessing classification and regression models are flawed.

Second, we define repeated cross-validation algorithms for selecting and assessing classification and regression models which deliver robust models and report the associated performance assessments.

We are aware of the following cross-validation pitfalls when selecting and assessing classification and regression models: Selection of variables prior to, and not within, cross-validation.