Exact(5)
The cerebellar model used in shape pattern recognition reduces model training time [18].
The base CNNs designed were tested according to Accuracy and the model training time required.
Of course, because of natural language processing constraints and machine learning model training time, this full vision is at least a couple of years out, according to Messina.
These models are able to increase the accuracy of the OFS breakdown prediction, as well as to reduce the model training time.
Furthermore, the enabled online learning allows an adaptive domain knowledge insertion and offers the advantage of reducing both the model training time and the information storage requirements of the overall system which makes it even more attractive for distributed sensor networks communication.
Similar(55)
To reduce the model complexity and training time, we propose a novel sparse Bayesian MIML learning model, which applies a RVM-like algorithm to obtain a sparse weighted combination for a set of basic learners.
We plot the RMSE of the final model and its training time in Figs. 4 and 5, respectively.
Experimental results show that, in terms of the model accuracy and training time, ELM with the logarithmic transformation is better than LS-SVM and RBFNN with/without the logarithmic transformation.
With DsIncr size as 50 K, an average of 3.90 models needed to be trained whereas with DsIncr size as 200 K, although we need to train only 3.15 models, each model training takes more time because of larger size of data.
It also observed that one-hidden-layer NN models have accuracy that is comparable to the two-hidden-layer NN models with less training time.
According to the results obtained in this research work, the BP model needed more time for training, while the ELM model recorded the shortest training time.
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