All Questions
7 questions
1vote
0answers
102views
Confused about use of random states for training models in scikit
I am new to ML and currently working on improving the accuracy of an MLPClassifier in scikit. My code looks like so ...
- 25
0votes
1answer
629views
Tuned model has higher CV accuracy, but a lower test accuracy. Should I use the tuned or untuned model?
I am working on a classification problem using Sci Kit Learn and am confused on how to properly tune hyper parameters to get the "best" model. Before any tuning, my logistic regression ...
0votes
1answer
1kviews
Is there any benefit to using cross validation from the XGBoost library over sklearn when tuning hyperparameters?
The XGBoost library has its own implementation of cross validation through xgboost.cv(). It looks like it requires data be stored as a DMatrix. Instead of using <...
- 101
0votes
1answer
686views
What does a leaf size of 1 in K-neighbors regression mean?
I am doing hyperparameter tuning + cross validation and I'm constantly getting that the optimal size of the leaf should be 1. Should I worry? Is this a sign of overfitting?
- 119
0votes
1answer
226views
Is Cross validation and GridSearchCV required every time we train a model?
I have a repetitive process that will build a model weekly based on the previous week's data. So while in development I tried GridSearchCV and cross-validation to ...
- 35
1vote
1answer
1kviews
Using Sklearn's predefined split
I am working on a binary classification task using SVM. The dataset is quite large so I don't want to use k-fold CV for parameter tuning, but instead a simple train-validation-test split. I have done ...
1vote
0answers
371views
How to put KerasClassifier, Hyperopt and Sklearn cross-validation together
I am performing a hyperparameter tuning optimization (hyperopt) tasks with sklearn on a Keras models. I am trying to optimize KerasClassifiers using the Sklearn cross-validation, Some code follows: <...
- 11
