GBM
Last updated
, generated by Sumble
Explore more → **GBM**
What is GBM?
GBM typically refers to Gradient Boosting Machines. It is a machine learning technique used for regression and classification tasks. It builds an ensemble of weak prediction models, typically decision trees, sequentially. Each new model corrects the errors made by the previous models, resulting in a strong predictive model. GBM is commonly used in various applications such as fraud detection, risk assessment, and predicting customer behavior.
What other technologies are related to GBM?
GBM Competitor Technologies
Attention-based models
No summary available
Attention-based models (typically neural networks) compete with GBM in various sequence-related and other tasks.
Random Forest
Random Forest is an ensemble learning method like GBM, and can be used for similar prediction tasks.
GLM
Generalized Linear Models are a class of models that can be used for similar tasks as GBM, though they have different assumptions and may perform better or worse depending on the dataset.
SVM
Support Vector Machines are a different type of machine learning model used for classification and regression, and therefore a competitor to GBM.
XGBoost
XGBoost is another gradient boosting framework and thus a direct competitor to GBM, often preferred due to optimizations and features.
Neural Nets
Neural Networks are a broad class of models that can be used for similar tasks to GBM, such as classification and regression. They may perform better or worse depending on the specific application.
LSTM
Long Short-Term Memory networks are a type of recurrent neural network and a competitor to GBM, especially in sequence prediction tasks.
RNN
Recurrent Neural Networks are a type of neural network and a competitor to GBM, especially in sequence prediction tasks.
Number of organizations that mention technology
267
GBM
17
Attention-based models
1,677
Random Forest
503
GLM
1,368
SVM
2,669
XGBoost
167
Neural Nets
1,196
LSTM
1,146
RNN
ⓘ Tap on a tech to explore matching organizations
GBM Complementary Technologies
Decision Tree
Decision trees are the base learners in GBM. GBM uses an ensemble of decision trees.
decision trees
Decision trees are the base learners in GBM. GBM uses an ensemble of decision trees.
NumPy
NumPy is a fundamental library for numerical computing in Python. GBM implementations often rely on NumPy for array operations.
Number of organizations that mention technology
ⓘ Tap on a tech to explore matching organizations
Which job functions commonly mention GBM?
Data Scientist
0.2% of all Data Scientist jobs mention GBM
View 479
jobs on Sumble
Pricing Analyst
0.1% of all Pricing Analyst jobs mention GBM
View 20
jobs on Sumble
Actuary
0.1% of all Actuary jobs mention GBM
View 29
jobs on Sumble
Machine Learning
23 Machine Learning jobs mention GBM
View 23
jobs on Sumble
Data Analyst
100 Data Analyst jobs mention GBM
View 100
jobs on Sumble
Which organizations are mentioning GBM?
Summary powered by 
Sumble
Sumble Find the right accounts, contact, message, and time to sell
Whether you're looking to get your foot in the door, find the right person to talk to, or close the deal — accurate, detailed, trustworthy, and timely information about the organization you're selling to is invaluable.
Use Sumble to: