![SOLVED: Use the scikit-learn traintestsplit function to create a Training-Test split with 75% of the data designated for training and 25% for testing. Make sure to use the random state provided below SOLVED: Use the scikit-learn traintestsplit function to create a Training-Test split with 75% of the data designated for training and 25% for testing. Make sure to use the random state provided below](https://cdn.numerade.com/ask_images/80426a3abe4040739d4731734e04d705.jpg)
SOLVED: Use the scikit-learn traintestsplit function to create a Training-Test split with 75% of the data designated for training and 25% for testing. Make sure to use the random state provided below
![model selection - Does it make sense to use train_test_split and cross-validation when using GridSearchCV to play with hyperparameters? - Data Science Stack Exchange model selection - Does it make sense to use train_test_split and cross-validation when using GridSearchCV to play with hyperparameters? - Data Science Stack Exchange](https://i.stack.imgur.com/PpBml.png)
model selection - Does it make sense to use train_test_split and cross-validation when using GridSearchCV to play with hyperparameters? - Data Science Stack Exchange
![3 Different Approaches for Train/Test Splitting of a Pandas Dataframe | by Angelica Lo Duca | Towards AI 3 Different Approaches for Train/Test Splitting of a Pandas Dataframe | by Angelica Lo Duca | Towards AI](https://miro.medium.com/v2/resize:fit:960/1*zwf6OQLk18Rt02EWOoupBQ.jpeg)