code: def false_negatives(mod, x, y):
      return (mod.predict(x) != y)[y == 0].sum()
  
imports: from pathlib import Path
  import matplotlib.pylab
  import seaborn
  import pandas
  import numpy
  from sklearn.pipeline import Pipeline
  from sklearn.datasets import make_blobs
  from sklearn.model_selection import GridSearchCV
  from sklearn.linear_model import LogisticRegression
  from sklearn.metrics import precision_score, recall_score, accuracy_score, make_scorer
  from sklego.meta import Thresholder
  import numpy
  import pandas
  import matplotlib.pylab
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import Pipeline, FeatureUnion
  from sklearn.preprocessing import OneHotEncoder, StandardScaler
  from sklearn.metrics import mean_absolute_error, mean_squared_error
  from sklego.datasets import load_chicken
  from sklego.preprocessing import ColumnSelector
  from sklego.meta import GroupedPredictor
  from sklearn.dummy import DummyRegressor
  from sklego.datasets import load_penguins
  from sklearn.preprocessing import StandardScaler
  from sklego.meta import GroupedTransformer
  import matplotlib.pylab
  import seaborn
  from sklego.datasets import make_simpleseries
  from sklearn.dummy import DummyRegressor
  from sklego.meta import GroupedPredictor, DecayEstimator
  from sklego.meta._decay_utils import exponential_decay, linear_decay, sigmoid_decay, stepwise_decay
  import numpy
  import matplotlib.pylab
  import seaborn
  from sklearn.metrics import confusion_matrix
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import LogisticRegression
  from sklearn.model_selection import GridSearchCV
  from sklego.meta import ConfusionBalancer
  from sklearn.utils import estimator_html_repr
  import numpy
  from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
  from sklearn.model_selection import cross_val_score
  from sklego.meta import ZeroInflatedRegressor
  import numpy
  from sklego.meta.outlier_classifier import OutlierClassifier
  from sklearn.ensemble import IsolationForest
  from sklearn.utils import estimator_html_repr
  from sklearn.ensemble import StackingClassifier, RandomForestClassifier
  from sklearn.utils import estimator_html_repr
label_desc: Use image node_id 3 for calling a global function with example usage: false_negatives(mod, x, y) and returns: unknown