The scikit-learn modules for different models
The scikit-learn library is organized into submodules. Each submodule contains algorithms and helper methods for a certain class of machine learning models and approaches.
Here is a sample of those submodules, including some example models:
Submodule |
Description |
Example models |
---|---|---|
cluster |
This is the unsupervised clustering |
KMeans and Ward |
decomposition |
This is the dimensionality reduction |
PCA and NMF |
ensemble |
This involves ensemble-based methods |
AdaBoostClassifier, AdaBoostRegressor, RandomForestClassifier, RandomForestRegressor |
lda |
This stands for latent discriminant analysis |
LDA |
linear_model |
This is the generalized linear model |
LinearRegression, LogisticRegression, Lasso and Perceptron ... |
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