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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