set_threshold

label

The probability threshold above which <code>label</code> will be
be predicted.

threshold

Refer to the Julia documentation for available parameters.

Julia Equivalent:
<a href="https://docs.interpretable.ai/v2.0.0/IAITrees/reference/#IAI.set_threshold!"><code>IAI.set_threshold!</code></a>

An interface to the algorithms of 'Interpretable AI'
<https://www.interpretable.ai> from the R programming language.
'Interpretable AI' provides various modules, including 'Optimal Trees' for
classification, regression, prescription and survival analysis, 'Optimal
Imputation' for missing data imputation and outlier detection, and 'Optimal
Feature Selection' for exact sparse regression. The 'iai' package is an
open-source project. The 'Interpretable AI' software modules are proprietary
products, but free academic and evaluation licenses are available.

Jack Dunn

Interface to 'Interpretable AI' Modules

Ying Zhuo

Interpretable AI LLC 

set_threshold function

Julia Equivalent:
<a href='https://docs.interpretable.ai/v2.0.0/IAITrees/reference/#IAI.set_threshold!'><code>IAI.set_threshold!</code></a>

For a binary classification problem, update the the predicted labels in the
leaves of the learner to predict a label only if the predicted probability is
at least the specified threshold. — set_threshold

For a binary classification problem, update the the predicted labels in the
leaves of the learner to predict a label only if the predicted probability is
at least the specified threshold.

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set_threshold: For a binary classification problem, update the the predicted labels in the leaves of the learner to predict a label only if the predicted probability is at least the specified threshold.

Description

Usage

Arguments

Examples