auto gluonKeyError: 'estimator'
时间: 2023-12-14 07:05:38 浏览: 32
这个错误通常是因为在使用AutoGluon时没有指定正确的模型估计器(estimator)。请确保在使用AutoGluon时指定了正确的估计器。例如,在使用`TabularPrediction`时,可以使用以下代码指定`estimator`:
```
from autogluon.tabular import TabularPrediction as task
predictor = task.fit(train_data='train.csv', label='class', eval_metric='accuracy', estimator='RF')
```
在这个例子中,我们指定了随机森林(RF)作为模型估计器。请检查你的代码,确保指定了正确的模型估计器。
相关问题
TypeError: estimator should be an estimator implementing 'fit' method
This error occurs when you pass an object that does not have a 'fit' method as an estimator to a machine learning model in scikit-learn.
The 'fit' method is a required method for any estimator in scikit-learn. It is used to train the model on the given data.
To resolve this error, make sure that the object you pass as an estimator has a 'fit' method. If you are creating a custom estimator, make sure it implements the 'fit' method.
def train(estimator): estimator.fit(X)
As an AI language model, I cannot give you the complete answer without knowing the context and the purpose of the code. However, based on the function name and the argument, it seems that this code is used for training a machine learning model.
The "estimator" is an object that represents a machine learning algorithm, such as a linear regression model or a decision tree model. The "fit" method is used to train the model on the input data X.
Therefore, this code trains the estimator on the input data X, which means that it adjusts the parameters of the model to minimize the difference between the predicted outputs and the actual outputs of the training data.