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Getting started

Installation

Install ATOM's newest release easily via pip:

$ pip install -U atom-ml

or via conda:

$ conda install -c conda-forge atom-ml

Note that these commands will also install all required dependencies. To install the optional dependencies as well, add [models] after the package's name.

$ pip install -U atom-ml[models]

Info

Since atom was already taken, download the package under the name atom-ml!



Usage

Call the ATOMClassifier or ATOMRegressor class and provide the data you want to use:

from sklearn.datasets import load_breast_cancer
from atom import ATOMClassifier

X, y = load_breast_cancer(return_X_y)
atom = ATOMClassifier(X, y, logger="auto", n_jobs=2, verbose=2)

ATOM has multiple data cleaning methods to help you prepare the data for modelling:

atom.impute(strat_num="knn", strat_cat="most_frequent", max_nan_rows=0.1)  
atom.encode(strategy="LeaveOneOut", max_onehot=8, frac_to_other=0.05)  
atom.feature_selection(strategy="PCA", n_features=12)

Train and evaluate the models you want to compare:

atom.run(
    models=["LR", "LDA", "XGB", "lSVM"],
    metric="f1",
    n_calls=25,
    n_initial_points=10,
    n_bootstrap=4,
)

Make plots to analyze the results: 

atom.plot_results(figsize=(9, 6), filename="bootstrap_results.png")  
atom.lda.plot_confusion_matrix(normalize=True, filename="cm.png")
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