我已经在一个名为 Modelrf 的类中编写了一个随机森林回归模型。它是一个单独的 Python 文件，命名为 RandomForest.py
RandomForest.py 的代码如下：
from sklearn.ensemble import RandomForestRegressorfrom sklearn.linear_model import LinearRegressionfrom sklearn.model_selection import train_test_splitimport numpy as npimport pandas as pdclass Modelrf(): def __init__(self, train = "train.csv", test = "test.csv"): self.X_train = pd.read_csv(train) self.X_test = pd.read_csv(test) self.linear_reg = LinearRegression() self.random_forest = RandomForestRegressor() def split(self): self.X_train.dropna(axis=0, subset=['salary'], inplace=True) self.X_test.dropna(axis=0, subset=['salary'], inplace=True) self.y_train = self.X_train.final_hourly_fee self.y_test = self.X_test.final_hourly_fee def fit(self): self.model = self.random_forest.fit(self.X_train, self.y_train) def predict(self): self.result = self.random_forest.predict(self.X_test) return self.resultif __name__ == '__main__': model_instance = Modelrf() model_instance.split() model_instance.fit() model_instance.predict() print(model_instance.result) print("Accuracy: ", model_instance.model.score(model_instance.X_test, model_instance.y_test)) output = pd.DataFrame({'Id': model_instance.X_test.index,'Y Original': model_instance.y_test, 'Y predicted':model_instance.result}) output.to_csv('outputTest.txt', index=False) 现在我已经将 Modelrf 类导入到 main.py 中
main.py 的代码如下：
我想在 GitLab 上启用 CI/CD，我应该如何编写 ‘.gitlab-ci.yml’ 文件的代码？
回答：
如果我理解正确的话，你需要进入你的仓库：设置 > CI/CD > 运行器。然后你需要决定是使用私有运行器还是共享运行器：
