title: Error ValueError: continuous is not supported when tried to use cross_val_score and Linear Regression
body: <p>I have used load_boston dataset from sklearn and Linear Regression.
  The code:</p>
  
  <pre><code>from sklearn.datasets import load_boston
  import pandas as pd
  import numpy as np
  %matplotlib inline
  from sklearn.model_selection import train_test_split, KFold,cross_val_score,cross_validate
  from sklearn.linear_model import LinearRegression
  
  #Loading the dataset
  x = load_boston()
  df = pd.DataFrame(x.data, columns = x.feature_names)
  df["MEDV"] = x.target
  X = df.drop("MEDV",1)   #Feature Matrix
  y = df["MEDV"]          #Target Variable
  df.head()
  
  linear = LinearRegression()
  X_train,X_test, y_train,y_test = train_test_split(X,y, random_state = 11)
  linear.fit(X_train,y_train)
  
  kfold = KFold(n_splits=5, random_state=11, shuffle=True)
  scores = cross_val_score(estimator= linear,cv=kfold, X=X, y = y, )# if scoring= "accuracy": error 
  </code></pre>
  
  <p>#>ValueError: continuous is not supported</p>
  
  <pre><code>print(f"Mean Accuracy: {scores.mean():.2%} and standard deviation: {scores.std():.2%}")
  </code></pre>
  
  <p>If I use <code>scoring= "accuracy"</code> in the cross_val_score, it rises a error:</p>
  
  <pre><code>ValueError: continuous is not supported
  </code></pre>
  
  <p>What is happening?</p>