Sentence examples for negative supervised from inspiring English sources

The EPs were only recruited after they performed 10 positive and 10 negative supervised scans to detect fracture.

In fact, all pairwise distances among labeled images (relevant and non-relevant) are updated according to a single factor λ. Notice that the supervised approach also exploits information provided by the set of non-relevant images, defining a set of negative supervised recommendations (line 11 of the Algorithm ??).

- Supervised and semi-supervised training – We distinguish between supervised and semi-supervised training.

Such an apparent overestimation of positive regulatory relationships was due to the fact that similar numbers of positive and negative examples in the supervised learning stage.

Based on the objective function and the maximum margin criterion, a dimensionality reduction algorithm, the non-negative sparse semi-supervised maximum margin algorithm, is proposed.

A non-negative sparse semi-supervised dimensionality reduction algorithm is proposed for hyperspectral data by making adequate use of a few labeled samples and a large number of unlabeled samples.

Negative consequences included increased supervision, breathalysing, delayed dispensing and supervised consumption of methadone.

We used these peaks as positive training cases, together with a set of randomly drawn control (anti-IgG) ChIP-seq peaks as negative training cases, to train supervised classifiers.

We experimentally validated 18 SRC-1 peak by quantitative PCR (qPCR) experiments (data not shown), which were used as positive training cases, together with a set of randomly drawn control (anti-IgG) ChIP-seq peaks as negative training cases, to train supervised classifiers.

Notably, SNORA31, -6, -62, and -71C also resulted significantly down-regulated in each of the CLL subgroups stratified according to genetic lesions (del13, del11, del17, 12+ and FISH negative) in a two-class supervised analysis with the N, MZ and SM group (data not shown).

The predictor is trained with known positive and negative instances in an approach called supervised learning.