docstr: Calculates the shortest distance from new_point to the line determined by start_point and end_point.
docstr_tok: ["Calculates","the","shortest","distance","from","new_point","to","the","line","determined","by","start_point","and","end_point","."]
code: def _distance_to_line(start_point, end_point, new_point):
      """
      Calculates the shortest distance from new_point to the line determined by start_point and end_point.
      """
      # for calculating elbow method
      return np.cross(
          new_point - start_point, end_point - start_point
      ) / np.linalg.norm(end_point - start_point)
  
imports: import time
  import numpy
  import pandas
  from sklearn.base import BaseEstimator
  from sklearn.feature_selection import SelectorMixin
  from sklearn.utils.validation import check_is_fitted
  import torch
  from nni.feature_engineering.feature_selector import FeatureSelector
  from .None import constants
  from .fginitialize import PrepareData
  from .fgtrain import _train
label_desc: Use image node_id 24 for calling the FeatureGradientSelector obj's underlying member method code with example usage: obj._distance_to_line(start_point, end_point, new_point) and returns: unknown