Figures 10 and 11 show the ROC curves for both classification analyses.
This classification analyses the values associated with the individual needs of a different group of users.
Using correspondence and ascending hierarchical classification analyses, homogenous groups were identified.
Classification analyses did not discriminate between study groups but this may be due to small study group sizes [13].
Discriminant and classification analyses demonstrate that full-resolution (1 nm) spectra provide very good spectral separation of the bottom-types.
Classification analyses were carried out comparing line orientations in V1, tone frequencies in A1, and responses from different fingers in M1.
The current work paves the way for wider adoption of spatiotemporal classification analyses, and greater use of MVPA with rapid ER designs.
Novel multivariate pattern classification analyses have enabled the prediction of decision outcomes from brain activity prior to decision-makers' reported awareness.
Classification analyses of the simulated sensor-specific spectra produce overall classification accuracy rates of 98%, 98%, 93%, 91%, 64%, 58%, and 50% for AAHIS, AVIRIS, Proto, CRESPO, Ikonos, Landsat-ETM+, and SPOT-HRV, respectively.
In this paper, we propose an environment recognition system for a wheeled mobile robot that consists of multiple classification analyses to make the robot more adaptive to various environments by selecting a suitable system such as decision making, navigation and controller using the result of the environment recognition system.
Primarily focusing on the Least Squares Single and Least Square All pattern estimators, we show that collinearities in the models, along with temporal autocorrelation, can cause false positive correlations between activation pattern estimates that adversely impact the false positive rates of pattern similarity and classification analyses.
