Sentence examples for applying supervised from inspiring English sources

Applying supervised learning in robot navigation encounters serious challenges such as inconsistent and noisy data, difficulty for gathering training data, and high error in training data.

Methods and results are presented for applying supervised machine learning techniques to the task of predicting the need for repairs of air compressors in commercial trucks and buses.

Applying supervised learning techniques to the annotated data, I found that a learner who makes use of these contextual cues can learn the inclusive as well as exclusive interpretation of disjunction from the language heard.

Here we demonstrate label-free prediction of DNA content and quantification of the mitotic cell cycle phases by applying supervised machine learning to morphological features extracted from brightfield and the typically ignored darkfield images of cells from an imaging flow cytometer.

LULC of the present area was extracted by applying supervised classification of LISS -IV image in ERDAS Imaging software.

Specifically, the proposed method first detects candidate spikes based on a mimetic approach, and afterwards classifies the candidate spikes by embedding the data in a low dimensional space and applying supervised classification in the embedding space.

Lastly, we applied supervised classification with Random Forests.

We use image analysis software9 to extract numerical measurements of cell morphology from the brightfield and darkfield images, and then we apply supervised machine-learning algorithms to identify cellular phenotypes of interest, in the present case, cell cycle phases.

Relying on big data technologies, we propose BIGBIOCL an algorithm that can apply supervised classification methods to datasets with hundreds of thousands of features.

Alternatively to folding, we apply supervised feature selection (as described in the "Methods" section) to limit the amount of fragments.

Pang et al. [4] apply supervised machine learning methods such as NB and SVM to sentiment classification.