0.16.0
Home
Installation
How to use this guide
Getting started
Support
User Guide
Tutorials
getML suite
Managing projects
Importing data
Annotating data
Data model
Preprocessing
Feature engineering
Predicting
Hyperparameter optimization
Deployment
API Documentation
Python API
Project management
Data handling
Database
Demo datasets
getML engine
Preprocessors
Feature learning
Predictors
LinearRegression
LogisticRegression
XGBoostClassifier
XGBoostRegressor
validate
booster
colsample_bylevel
colsample_bytree
gamma
learning_rate
max_delta_step
max_depth
min_child_weights
n_estimators
n_jobs
normalize_type
num_parallel_tree
objective
one_drop
rate_drop
reg_alpha
reg_lambda
sample_type
silent
skip_drop
subsample
type
Pipeline
Hyperopt
Command line interface
About
getML
Docs
»
Python API
»
getml.predictors
»
XGBoostRegressor
»
reg_lambda
reg_lambda
¶
XGBoostRegressor.
reg_lambda
:
float
=
1.0
¶