class_docstr: Sigmoid regression model.
  
  Attributes
  ----------
  a_ : float
      The slope.
  
  b_ : float
      The intercept.
class_docstr_tok: ["Sigmoid","regression","model",".","Attributes","--","--","--","--","--","a_",":","float","The","slope",".","b_",":","float","The","intercept","."]
docstr: Fit the model using X, y as training data.
  
  Parameters
  ----------
  X : array-like, shape (n_samples,)
      Training data.
  
  y : array-like, shape (n_samples,)
      Training target.
  
  sample_weight : array-like, shape = [n_samples] or None
      Sample weights. If None, then samples are equally weighted.
  
  Returns
  -------
  self : object
      Returns an instance of self.
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code: def fit(self, X, y, sample_weight=None):
      """Fit the model using X, y as training data.
  
      Parameters
      ----------
      X : array-like, shape (n_samples,)
          Training data.
  
      y : array-like, shape (n_samples,)
          Training target.
  
      sample_weight : array-like, shape = [n_samples] or None
          Sample weights. If None, then samples are equally weighted.
  
      Returns
      -------
      self : object
          Returns an instance of self.
      """
      X = column_or_1d(X)
      y = column_or_1d(y)
      X, y = indexable(X, y)
  
      self.a_, self.b_ = _sigmoid_calibration(X, y, sample_weight)
      return self
  
imports: from __future__ import division
  import warnings
  from math import log
  import numpy
  from scipy.optimize import fmin_bfgs
  from sklearn.preprocessing import LabelEncoder
  from .base import BaseEstimator, ClassifierMixin, RegressorMixin, clone
  from .preprocessing import label_binarize, LabelBinarizer
  from .utils import check_X_y, check_array, indexable, column_or_1d
  from .utils.validation import check_is_fitted
  from .utils.fixes import signature
  from .isotonic import IsotonicRegression
  from .svm import LinearSVC
  from .model_selection import check_cv
  from .metrics.classification import _check_binary_probabilistic_predictions
label_desc: Use image node_id 1 for calling the _SigmoidCalibration obj's underlying member method code with example usage: obj.fit(X, y, sample_weight) and returns: self