Sentence examples for boosted methods from inspiring English sources

We saw a broad range of approaches, from generalised boosted methods to random forests, single value decomposition to matrix factorisation and collaborative filtering, with no one class of model outperforming all the others.

Here, all boosting methods are based on decision tree for the comparison of performance.

The other notations are consistent with the ones in other mentioned boosting methods.

Recently, boosting methods, originally proposed by Freund and Shapire [5], have gained much attention.

Although the SVM and boosting methods are the fine classifiers, their results are slightly poorer than our MHMM + Inv method (see Figure 11).

It develops the model in a sequential stage-wise fashion like other boosting methods do, and generalizes them by allowing optimization of an arbitrary differentiable loss function.

In an unbiased experiment, we clearly show that the gain of boosting methods compared to a single hidden Markov model is in all cases only marginal, while bagging significantly outperforms all other methods.

We implemented adaptive boosting methods of [9, 11], and [10], and constructed an ensemble of linear classifiers for each of them to compare them against ours under the same platform.

The chapter starts by considering simple techniques for efficient face detection, including those based on detection of features such as eyes, nose, and mouth, and moves on to the use of boosting methods for rapid whole face detection.

In general, elastic net identified a greater number of significant genes than Lasso and boosting methods.

Elastic net identified 33 genes in total, whereas the Lasso and boosting methods identified 6 and 8 genes, respectively.