A lightweight automl library
Project description
CutoML is a lightweight automl library, highly optimized to give you the best possible model depending on your datasets very quickly.
Installation
pip install -U cutoml
Usage Example
For classification,
from cutoml.cutoml import CutoClassifier
from sklearn.model_selection import train_test_split
from sklearn import datasets
dataset = datasets.load_digits()
X_train, X_test, y_train, y_test = train_test_split(dataset.data,
dataset.target,
test_size=0.25)
ctc = CutoClassifier(k_folds=5, n_jobs=2)
ctc.fit(X=X_train, y=y_train)
For regression,
from cutoml.cutoml import CutoRegressor
from sklearn.model_selection import train_test_split
from sklearn import datasets
dataset = datasets.load_boston()
X_train, X_test, y_train, y_test = train_test_split(dataset.data,
dataset.target,
test_size=0.25)
ctr = CutoRegressor(k_folds=5, n_jobs=2)
ctr.fit(X=X_train, y=y_train)
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