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We used a popular modeling approach, called boosted regression trees (BRTs), where many simple models are iteratively fit to a random subset of the data (bag fraction) and are combined to better estimate a response27,28.
Each block of data is a data bag produced by grouping a set of tuples.
For example, in Seer data, we may have a data bag shown in Table 4.
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Then another speaker, this time from ExxonMobil Chemical, asserted that – based on the latest life-cycle assessment data – shopping bags made out of high density polyethylene (HDPE) are the sustainable option.
A UDF Java program reads the data as bags and converts them back to tuples, named (ADJUST.java).
At each bootstrap resampling step, 2/3 of the data (in-bag) were selected to build the decision tree.
In summary, we propose using ranking value of microarray data and bagging with sequential hypothesis testing to dynamically determine the number of classifiers required.
Our data implicate BAG-1 as a key player in oncogenic transformation by Raf and identify it as a potential molecular target for cancer treatment.
In addition, a recently published study [ 38] analyzed expression data from bag-of-marbles (bam) mutant testes [ 39]. bam mutations block entry into meiosis and result in overgrowth of primary spermatocytes [ 40].
For example, only BAG-1L regulates the AR (Froesch et al, 1998) and ER (R Cutress, PA Townsend and G Packham, unpublished data) whereas both BAG-1L and BAG-1M regulate the GR.
First, we only keep the image bag data with lateral, dorsal and ventral view information.
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