Sentence examples for reducing the prediction from inspiring English sources

The main objective of the training process is to optimize the connection weights that contribute toward reducing the prediction errors between the predicted and actual target values to a satisfactory level (the preset error goal).

Through reducing the prediction model, the corresponding MPC controller exhibits less on-line computational burden, and thus becomes more applicable in practice.

Inspired by the machine learning (ML) theory through which the models are learned based on large amounts of observed data and the prediction is conducted without explicitly modeling space objects and space environment, the proposed ML approach integrates physics-based orbit prediction algorithms with a learning-based process that focuses on reducing the prediction errors.

The assumption that clinical terms are equally relevant to a disease is unrealistic, reducing the prediction accuracy.

Random Forest pools together many noisy but approximatively unbiased models, hence, reducing the predictions variance.

Comparing with Sachnev et al.'s noncausal double-set prediction method [15], the proposed prediction method can further reduce the prediction errors by predicting data in a single pass (which avoids the distortion problem due to the fact that half of the pixels in the second set predicted with the watermarked pixels in the first set).

Noncausal predictive ways are beneficial to reduce the prediction errors for image vector quantization coding [28, 29] and speech compression [31].

The SNPs in GBLUP predict relationships over long genetic distances, which reduces the prediction error variance and increases bias but apparently not to the point that the haplotype models are clearly favoured.

If the predicted values were beyond the error range, a recursive algorithm could be introduced to reduce the prediction error.

The location prediction strategies were also considered to reduce the prediction errors to save power.

The experimental results have revealed that the non-rating attributes contributed to reduce the prediction errors.