code: def adjusted_rsquared(r2, n, p):
      return 1 - (1 - r2) * ((n - 1) / (n - p - 1))
  
imports: import numpy
  import pandas
  from tqdm import tqdm
  import datetime
  import time
  from sklearn.pipeline import Pipeline
  from sklearn.impute import SimpleImputer, MissingIndicator
  from sklearn.preprocessing import StandardScaler, OneHotEncoder, OrdinalEncoder
  from sklearn.compose import ColumnTransformer
  from sklearn.utils import all_estimators
  from sklearn.base import RegressorMixin
  from sklearn.base import ClassifierMixin
  from sklearn.metrics import accuracy_score, balanced_accuracy_score, roc_auc_score, f1_score, r2_score, mean_squared_error
  import warnings
  import xgboost
  import lightgbm
label_desc: Use image node_id 2 for calling a global function with example usage: adjusted_rsquared(r2, n, p) and returns: unknown