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Despite the benefits mentioned, this data transformation introduced a computational limitation due to the enormous amount of feature combinations to be processed, especially when N-feature model classifiers for N>4 are considered (If 100 features are selected, and 10-feature model classifier is investigated, the search space will be C10= 1.731030945644000 × 1013 different combination of features).
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For all alloys, the α↔γ phase transformation introduces a volume change of 1.0%.
Moreover, the physical iterative transformation between crystalline and amorphous phase transformation introduces a swelling and deswelling effect.
The crucial step of transformation introduces a clear unbalance in the Vitamin D signalling and metabolic pathways.
The transformation introduces an elliptic boundary value problem which is solved by a preconditioned conjugate gradient method.
The techniques we use build on a time transformation introduced in previous work.
The transformation introduced is proved to be bijective.
Please note, the experimental results in [10] also showed that the Pig transformation introduces performance degeneration with a performance ratio of 1.5 (the running time of Pig program/the running time of a Java Map-Reduce program) on average.
We prove that the transformation introducing such coordinates maps analytically a complex ball of radius R/Nα (in discrete Sobolev-analytic norms) into a ball of radius R′/Nα (with R,R′>0 independent of N) if and only if α≥2.
Transformation experiments have introduced a hemagglutinin glycoprotein [ 70] and a novel chimeric polyepitope antigen [ 71], both for neutralizing immunization against measles virus into the carrot nuclear genome.
This transformation introduces odd powers of x and y to this polynomial.
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