|
gptkbp:instance_of
|
gptkb:software_framework
|
|
gptkbp:community_support
|
active community
|
|
gptkbp:controls
|
large datasets
|
|
gptkbp:developed_by
|
gptkb:Microsoft
|
|
gptkbp:has_documentation
|
available online
|
|
gptkbp:has_feature
|
cross-validation
early stopping
feature importance
categorical feature support
|
|
gptkbp:has_method
|
gptkb:High_School
objective
learning_rate
max_depth
num_leaves
min_data_in_leaf
boosting_type
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Light GBM
|
|
gptkbp:is_compatible_with
|
gptkb:Java
gptkb:R
gptkb:Library
gptkb:C#
|
|
gptkbp:is_effective_against
|
high-dimensional data
|
|
gptkbp:is_open_source
|
gptkb:theorem
|
|
gptkbp:is_optimized_for
|
gptkb:benchmark
|
|
gptkbp:is_part_of
|
gptkb:Database_Management_System
gptkb:Azure_Machine_Learning
gptkb:Microsoft_ML._NET
|
|
gptkbp:is_popular_in
|
data science community
|
|
gptkbp:is_scalable
|
gptkb:theorem
|
|
gptkbp:is_used_for
|
gptkb:video_game
gptkb:computer
regression
gradient boosting
|
|
gptkbp:is_used_in
|
image processing
financial modeling
natural language processing
healthcare analytics
Kaggle competitions
marketing analytics
|
|
gptkbp:language
|
gptkb:C++
|
|
gptkbp:performance
|
gptkb:Linear_Regression
gptkb:Support_Vector_Machines
gptkb:Cat_Boost
gptkb:Random_Forest
XG Boost
|
|
gptkbp:provides
|
high efficiency
fast training speed
|
|
gptkbp:security_features
|
overfitting
|
|
gptkbp:suitable_for
|
large-scale machine learning
|
|
gptkbp:supports
|
distributed learning
parallel learning
|
|
gptkbp:uses
|
histogram-based learning
|
|
gptkbp:bfsParent
|
gptkb:ML._NET
gptkb:Gradient_Boosting_Machines
gptkb:DGX_A100
gptkb:Seldon_Core
gptkb:Gradient_Boosted_Trees
|
|
gptkbp:bfsLayer
|
5
|