But he added that subsequent classification analysis showed that it was littered with state secrets, many of them major.
It means to improve the performance of subsequent classification algorithms.
If the user decides to change the direction, a subsequent classification is performed to decide turn left or right.
A subset of the weighted features is thus selected as the best subset for subsequent classification of the data.
A human face with thousands of pixels, if represented immediately, needs a huge dimensional space for statistical analysis and subsequent classification.
Since thematically similar documents will exhibit nearly similar distributions over the latent topics, the latter can be used as intermediate or high-level features for subsequent classification.
Supervised TSL algorithms use concept-driven dimensionality reduction to achieve discriminant tensor subspaces by considering the subsequent classification or recognition tasks.
The effects of scaling remotely sensed data, prior to PCA, in terms of subsequent classification accuracy, have been investigated by many including [23, 49 51].
The distribution (and subsequent classification) was not sensitive to whether or not we omitted the above imputation procedure for small-celled occupations.
In fact, the clustering learning in these algorithms just aids the subsequent classification learning and does not benefit from the latter.
When correlating the samples with the corresponding class labels, canonical correlation analysis (CCA) can be used for supervised feature extraction and subsequent classification.
