class_docstr: Sigmoid regression model.
  
  Attributes
  ----------
  a_ : float
      The slope.
  
  b_ : float
      The intercept.
docstr: Predict new data by linear interpolation.
  
  Parameters
  ----------
  T : array-like of shape (n_samples,)
      Data to predict from.
  
  Returns
  -------
  T_ : ndarray of shape (n_samples,)
      The predicted data.
docstr_tok: ["Predict","new","data","by","linear","interpolation",".","Parameters","--","--","--","--","--","T",":","array-like","of","shape","(","n_samples",",",")","Data","to","predict","from",".","Returns","--","--","--","-","T_",":","ndarray","of","shape","(","n_samples",",",")","The","predicted","data","."]
code: def predict(self, T):
      """Predict new data by linear interpolation.
  
      Parameters
      ----------
      T : array-like of shape (n_samples,)
          Data to predict from.
  
      Returns
      -------
      T_ : ndarray of shape (n_samples,)
          The predicted data.
      """
      T = column_or_1d(T)
      return expit(-(self.a_ * T + self.b_))
  
imports: import warnings
  from functools import partial
  from inspect import signature
  from math import log
  from numbers import Integral, Real
  import numpy
  from scipy.optimize import fmin_bfgs
  from scipy.special import expit, xlogy
  from sklearn.utils import Bunch
  from .base import BaseEstimator, ClassifierMixin, MetaEstimatorMixin, RegressorMixin, _fit_context, clone
  from .isotonic import IsotonicRegression
  from .model_selection import check_cv, cross_val_predict
  from .preprocessing import LabelEncoder, label_binarize
  from .svm import LinearSVC
  from .utils import _safe_indexing, column_or_1d, indexable
  from .utils._param_validation import HasMethods, Hidden, Interval, StrOptions, validate_params
  from .utils._plotting import _BinaryClassifierCurveDisplayMixin
  from .utils.metadata_routing import MetadataRouter, MethodMapping, _routing_enabled, process_routing
  from .utils.multiclass import check_classification_targets
  from .utils.parallel import Parallel, delayed
  from .utils.validation import _check_fit_params, _check_pos_label_consistency, _check_sample_weight, _num_samples, check_consistent_length, check_is_fitted
label_desc: Use image node_id 2 for calling the _SigmoidCalibration obj's underlying member method code with example usage: obj.predict(T) and returns: expit