lgb_shared_dataset_params

vector of labels to use as the target variable

label

weight

initial score is the base prediction lightgbm will boost from

init_score

used for learning-to-rank tasks. An integer vector describing how to
group rows together as ordered results from the same set of candidate results
to be ranked. For example, if you have a 100-document dataset with
<code>group = c(10, 20, 40, 10, 10, 10)</code>, that means that you have 6 groups,
where the first 10 records are in the first group, records 11-30 are in the
second group, etc.

group

a list of information of the <code>lgb.Dataset</code> object. NOTE: use of <code>info</code>
is deprecated as of v3.3.0. Use keyword arguments (e.g. <code>init_score = init_score</code>)
directly.

info

Parameter docs for fields used in <code>lgb.Dataset</code> construction

internal

Tree based algorithms can be improved by introducing boosting frameworks.
'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>.
This package offers an R interface to work with it.
It is designed to be distributed and efficient with the following advantages:
1. Faster training speed and higher efficiency.
2. Lower memory usage.
3. Better accuracy.
4. Parallel learning supported.
5. Capable of handling large-scale data.
In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions.
Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple machines.

Yu Shi

lightgbm

Light Gradient Boosting Machine

Guolin Ke

Damien Soukhavong

James Lamb

Qi Meng

Thomas Finley

Taifeng Wang

Wei Chen

Weidong Ma

Qiwei Ye

Tie-Yan Liu

Nikita Titov

Yachen Yan

Microsoft Corporation 

Dropbox, Inc. 

Jay Loden

Dave Daeschler

Giampaolo Rodola

Alberto Ferreira

Daniel Lemire

Victor Zverovich

IBM Corporation 

David Cortes

lgb_shared_dataset_params function

<dl><dt>label</dt>
<dd>vector of labels to use as the target variable</dd>
<dt>weight</dt>
<dd>numeric vector of sample weights</dd>
<dt>init_score</dt>
<dd>initial score is the base prediction lightgbm will boost from</dd>
<dt>group</dt>
<dd>used for learning-to-rank tasks. An integer vector describing how to
group rows together as ordered results from the same set of candidate results
to be ranked. For example, if you have a 100-document dataset with
<code>group = c(10, 20, 40, 10, 10, 10)</code>, that means that you have 6 groups,
where the first 10 records are in the first group, records 11-30 are in the
second group, etc.</dd>
<dt>info</dt>
<dd>a list of information of the <code>lgb.Dataset</code> object. NOTE: use of <code>info</code>
is deprecated as of v3.3.0. Use keyword arguments (e.g. <code>init_score = init_score</code>)
directly.</dd></dl>

Arguments

Shared Dataset parameter docs — lgb_shared_dataset_params

<dl>

<dt>label</dt>
<dd>vector of labels to use as the target variable</dd>


<dt>weight</dt>
<dd>numeric vector of sample weights</dd>


<dt>init_score</dt>
<dd>initial score is the base prediction lightgbm will boost from</dd>


<dt>group</dt>
<dd>used for learning-to-rank tasks. An integer vector describing how to
group rows together as ordered results from the same set of candidate results
to be ranked. For example, if you have a 100-document dataset with
<code>group = c(10, 20, 40, 10, 10, 10)</code>, that means that you have 6 groups,
where the first 10 records are in the first group, records 11-30 are in the
second group, etc.</dd>


<dt>info</dt>
<dd>a list of information of the <code>lgb.Dataset</code> object. NOTE: use of <code>info</code>
is deprecated as of v3.3.0. Use keyword arguments (e.g. <code>init_score = init_score</code>)
directly.</dd>

</dl>

Shared Dataset parameter docs

lgb_shared_dataset_params: Shared Dataset parameter docs

Description

Arguments