Sentence examples for maximum tree depth from inspiring English sources

The dataset signals are combined with a supervised learning model, that is a Decision Tree Regressor [17], where we have set a maximum tree depth equal to 3 and trained and tested using the Leave-One-Out Error [18] technique which has been theoretically shown to be an unbiased estimator of generalisation error.

We use the supervised Random Forest classifier (best performance achieved with 45 tree estimators, allowing for a maximum tree depth = 25 each) to predict links from one layer using features from the other.

The process continues with the left and the right child using the corresponding training sets PL and PR until a leaf is created when either the maximum tree depth is reached, or less than a minimum number of training samples are left [21].

The maximum tree depth was set to 7. Hypotheses were scored using the default survival formula.

RP Single Trees had a minimum of ten samples per node and a maximum tree depth of 20.

The minimum distance between any two sites was set to 2 Å, and the maximum tree depth was set to 4 with a final box size of 1 Å.

We derive the performance bounds for minimum server load, maximum streaming rate, and minimum tree depth under different peer selection constraints.

We limited model sizes to a maximum number of 16 internal nodes resulting in a maximum of 17 patient groups and a tree depth of 5 corresponding to a maximum of 5 rules to classify patients.

Further parameter settings were: tree depth of 2, relative abundance cutoff of 1, and maximum report number of 100.

Their maximum tree heights differed.

The optimal classifier is constructed with 3950 trees (tree depth is 1).