Sentence examples for training classification from inspiring English sources

The average training classification accuracy obtained is 76.88% and the success rate of the simulated robot arm reaching the target is 85%.

Here we present an approach for change-based LCTS development following from previous research, but with significant advancements in change detection, training, classification, and evidence-based refinement.

After several SVM training experiments, it was decided to use the RBF kernel, that is, is, and ; these parameters achieve a high training classification rate of about 93%.

Our method contains four stages; the feature extraction stage follows the Bag-of-Features (BoF) framework, but it introduces significantly novel stages in the training, classification and ensemble stages.

After several SVM training experiments, it was decided to use the RBF kernel, that is, is, and, where these parameters achieve a high training classification rate of close to 93%.

We note that the SVMs trained with 256-dimensional raw AE data had quite poor performance, where the AUC was 0.39 and 0.31 for datasets SR1 and SR2. Figure 10 The training classification performance of different feature sets on the dataset SR1 (a) and SR2 (b).

The majority of case managers were aged 40 years or older, 90% (n = 160) were female and 42% (n = 75) were from a nursing training background, although there was a wide variation in their training classifications (Table  1).

A subset of samples are used to train classification modules.

A wide range of segmentation techniques use quantitative image texture features to train classification algorithms.

We try to help automating this process by implementing a segmentation algorithm based on the previously trained classification models.

It is expensive to manually label a large amount of ADR related messages (positive examples) and non-ADR related messages (negative examples) to train classification systems.