The study reveals the suitability of the extra tree classifier for breast cancer classification. The model is compared with other state of art models and it was seen to be superior in performance. Furthermore,
We introduce the extremely randomized trees (ERT), the multivariate adaptive regression splines (MARS), the M5 Model tree (M5Tree) the random forest (RF), and the multilayer perceptron neural network (MLPNN) models, which were compared to the air2stream model, using large data set collected ...
The integration of deep learning and machine learning in the Multilayer Extremely Randomized Tree Learning Machine (MERTLM) model represents a departure from traditional approaches and a significant advancement in the field of medical categorization accuracy. The MERTLM approach integrates randomized tree ...
Study Population: Extremely or very preterm-born children aged 7 to 15 years, previously randomized to receive either high-dose rhEPO or placebo in the perinatal period. Inclusion criteria: participation in an ongoing neuropediatric study (EpoKids), written informed consent. Exclusion criteria: previo...
The GPS satellites having an orbital period of 12 hours, we also randomized the initial trajectory time to get different satellite positions. 3.2. Environments setup As stated earlier, our dataset aims to provide data to train and test algorithms for ...
Pfab F, Huss-Marp J, Gatti A, Fuqin J, Athanasiadis GI, Irnich D, Raap U, Schober W, Behrendt H, Ring J, Darsow U: Influence of acupuncture on type I hypersensitivity itch and the wheal and flare response in adults with atopic eczema - a blinded, randomized, placebo-controlled, cr...
The therapy presented in the current case reports presents a potential option for improvement in these patients. Prospective clinical studies and randomized clinical trials that will further determine the effectiveness in a large group of patients and assess immunological changes are warranted....
Among the three ensemble methods, the Extremely Randomized Tree technique has better outcomes with the accuracy of 98% for positive and 85% for negative cases, with an overall accuracy of 96.8%. The error rate of all the three ensemble classifiers is also under 0.5% which uncovers that ...
We proposed and compared two methods namely, extremely randomized tree (ERT) and random forest (RF) models. To demonstrate the usefulness and robustness of the proposed models, a result using the MLR models was also provided for further comparison. The models were developed using several water ...
Extremely randomized treesPredictive clustering treesIn this work, we address the task of learning ensembles of predictive models for predicting multiple continuous variables, i.e., multitarget regression (MTR). In contrast to standard regression, where the output is a single scalar value, in MTR ...