1  API CheatSheet
 2  ==============
 3  
 4  The full API Reference is split by modality: :doc:`pyod.models.tabular`, :doc:`pyod.models.timeseries`, :doc:`pyod.models.graph`, :doc:`pyod.models.embedding`, :doc:`pyod.ad_engine`, and :doc:`pyod.utils`. Below is a quick cheatsheet for the shared detector API:
 5  
 6  * :func:`pyod.models.base.BaseDetector.fit`: The parameter y is ignored in unsupervised methods.
 7  * :func:`pyod.models.base.BaseDetector.decision_function`: Predict raw anomaly scores for X using the fitted detector.
 8  * :func:`pyod.models.base.BaseDetector.predict`: Determine whether a sample is an outlier or not as binary labels using the fitted detector.
 9  * :func:`pyod.models.base.BaseDetector.predict_proba`: Estimate the probability of a sample being an outlier using the fitted detector.
10  * :func:`pyod.models.base.BaseDetector.predict_confidence`: Assess the model's confidence on a per-sample basis (applicable in predict and predict_proba) :cite:`a-perini2020quantifying`.
11  
12  
13  **Key Attributes of a fitted model**:
14  
15  * :attr:`pyod.models.base.BaseDetector.decision_scores_`: Outlier scores of the training data. Higher scores typically indicate more abnormal behavior. Outliers usually have higher scores.
16    Outliers tend to have higher scores.
17  * :attr:`pyod.models.base.BaseDetector.labels_`: Binary labels of the training data, where 0 indicates inliers and 1 indicates outliers/anomalies.
18  
19  
20  See base class definition below:
21  
22  pyod.models.base module
23  -----------------------
24  
25  .. automodule:: pyod.models.base
26      :members:
27      :undoc-members:
28      :show-inheritance:
29      :inherited-members:
30