text: import numpy as np
  import pandas as pd
  from comet_ml import Experiment
  from sklearn import tree
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import load_iris
  
  
  experiment = Experiment(
      api_key=input('api key: '),
      project_name=input('project name: '),
      workspace=input('workspace: '),
  )
  
  X, y = load_iris(return_X_y=True)
  X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.2)
  clf = tree.DecisionTreeClassifier()
  clf = clf.fit(X_train, y_train)
  experiment.log_metric('accuracy', clf.score(X_test, y_test))
  