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Showing 1 to 2 of 2 for “"extremely randomized trees"”.

  1. Terrain characterization for site selection and preparation

    … models, support vector machine (SVM) and extremely randomized trees (ET), were paired with 5 input variables. The results indicated that SMC could be predicted with greater accuracy by reducing the dimensionality of a hyperspectral dataset to resemble a standard multispectral dataset. The …

    uiuc Repository record for Terrain characterization for site selection and preparation (opens in a new tab)

  2. Metagenomic Data Analysis Using Extremely Randomized Tree Algorithm

    … In this study, an effective methodology, using Extremely Randomized Trees (ET) Algorithm, was formulated and demonstrated to capture such ARG variations and identify discriminatory ARGs among environmentally derived metagenomes. In this study, data were grouped by: geographic location (to …

    vt Repository record for Metagenomic Data Analysis Using Extremely Randomized Tree Algorithm (opens in a new tab)