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API Docs / Microsoft.VisualBasic.Math.Statistics / ShapAlgo1

ShapAlgo1

Full name Microsoft.VisualBasic.Math.Statistics.ShapleyValue.TreeShap.ShapAlgo1 Assembly Microsoft.VisualBasic.Math.Statistics Members 8

See https://arxiv.org/pdf/1802.03888.pdf - Chapter 3.1, Algorithm 1.

v - vector of node values; = "internal" for internal nodes a,b - left and right node indexes for each internal node t - thresholds for each internal node d - indexes of the features used for splitting in internal nodes r - cover of each node (ie. how many data samples fall in that sub-tree) w - weight, measures the proportion of the training samples matching the conditioning set S fall into each leaf s - set of non-zero indexes in z', ie. known features z' - for each feature, 0 if unknown, 1 if known x - feature values

00 Remarks

https://github.com/pkozelka/treeshap

01 Syntax

Microsoft.VisualBasic.Math.Statistics.ShapleyValue.TreeShap.ShapAlgo1

02 Methods

NameOverloadsSummary
expValue 1 sincerely, I have no idea what this thing computes; I expected one computed contribution weight per feature, and instead, this computes just one number.

03 Fields

NameOverloadsSummary
x 1 feature values
v 1 vector of node values; = "internal" for internal nodes
t 1 thresholds for each internal node
r 1 cover of each node (ie.
a 1 left and right node indexes for each internal node
b 1 left and right node indexes for each internal node
d 1 indexes of the features used for splitting in internal nodes

04 Members

method expValue #
expValue

sincerely, I have no idea what this thing computes; I expected one computed contribution weight per feature, and instead, this computes just one number. Probably needs to be called repeatedly; more study of the paper needed here.

field x #
x

feature values

field v #
v

vector of node values; = "internal" for internal nodes

field t #
t

thresholds for each internal node

field r #
r

cover of each node (ie. how many data samples fall in that sub-tree)

field a #
a

left and right node indexes for each internal node

field b #
b

left and right node indexes for each internal node

field d #
d

indexes of the features used for splitting in internal nodes