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Table 2 BinomialRF improves the memory requirements

From: binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions

Features dimension Interaction order Memory requirements for interactions Memory efficiency
binomialF Other methods of Table 1
10 2 N ×  10 N ×  55 ~  5
3 N ×  175 ~  17
100 2 N × 100 N ×  5050 ~  50
3 N ×  166,750 ~  1700
1000 2 N × 1000 N ×  500,500 ~  500
3 N × 166,667,500 ~  170,000
  1. The improvement is on the orders of magnitude in 2-way and 3-way interactions when compared to other methods of Table 1. One advantage of the binomialRF algorithm is that it can screen for sets of gene interactions in a memory efficient manner by only requiring a constant-sized matrix whereas the current state of the art requires the predictor matrix to increase in size in a combinatoric fashion to screen for interactions. Memory efficiency is defined by \( \raisebox{1ex}{$\mathrm{Dim}\ \left(\otimes {X}_{i=1}^K\right)$}\!\left/ \!\raisebox{-1ex}{$ Dim(X)$}\right. \), and interaction memory requirements are defined by the number of columns required to map all k-way interactions