源码

#set up the linear regression model
from sklearn.linear_model import LinearRegression
LR1 = LinearRegression()
#train the model
LR1.fit(X,y)

#calculate the price vs size
y_predict_1 = LR1.predict(X)
print(y_predict_1)


#evaluate the model
from sklearn.metrics import mean_squared_error,r2_score,accuracy_score
mean_squared_error_1 = mean_squared_error(y,y_predict_1)
r2_score_1 = r2_score(y,y_predict_1)
accuracy_score_1 = accuracy_score(y,y_predict_1)

accuracy_score_1

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/var/folders/t0/ql_4wyl17tg2m1qmgf7k62fm0000gn/T/ipykernel_98298/1665350966.py in <module>
      3 mean_squared_error_1 = mean_squared_error(y,y_predict_1)
      4 r2_score_1 = r2_score(y,y_predict_1)
----> 5 accuracy_score_1 = accuracy_score(y,y_predict_1)
      6 # print(y,type(y_predict_1[0]))
      7 print(mean_squared_error_1,r2_score_1)

~/opt/miniconda3/lib/python3.8/site-packages/sklearn/metrics/_classification.py in accuracy_score(y_true, y_pred, normalize, sample_weight)
    203 
    204     # Compute accuracy for each possible representation
--> 205     y_type, y_true, y_pred = _check_targets(y_true, y_pred)
    206     check_consistent_length(y_true, y_pred, sample_weight)
    207     if y_type.startswith("multilabel"):

~/opt/miniconda3/lib/python3.8/site-packages/sklearn/metrics/_classification.py in _check_targets(y_true, y_pred)
    102     # No metrics support "multiclass-multioutput" format
    103     if y_type not in ["binary", "multiclass", "multilabel-indicator"]:
--> 104         raise ValueError("{0} is not supported".format(y_type))
    105 
    106     if y_type in ["binary", "multiclass"]:

ValueError: continuous is not supported

想看看正确分数，不知道这个问题怎么造成的，类型一样，shape一样，可能我犯了一个低级错误，但是检查不出来，请老师帮忙看一下，谢谢🙏