sklearn.isotonic.isotonic_regression¶
- sklearn.isotonic.isotonic_regression(y, *, sample_weight=None, y_min=None, y_max=None, increasing=True)[source]¶
Solve the isotonic regression model.
Read more in the User Guide.
- Parameters:
- yarray-like of shape (n_samples,)
The data.
- sample_weightarray-like of shape (n_samples,), default=None
Weights on each point of the regression. If None, weight is set to 1 (equal weights).
- y_minfloat, default=None
Lower bound on the lowest predicted value (the minimum value may still be higher). If not set, defaults to -inf.
- y_maxfloat, default=None
Upper bound on the highest predicted value (the maximum may still be lower). If not set, defaults to +inf.
- increasingbool, default=True
Whether to compute
y_is increasing (if set to True) or decreasing (if set to False).
- Returns:
- y_ndarray of shape (n_samples,)
Isotonic fit of y.
References
“Active set algorithms for isotonic regression; A unifying framework” by Michael J. Best and Nilotpal Chakravarti, section 3.