Help Understanding Cross Validation and Decision Trees
I've been reading up on Decision Trees and Cross Validation, and I understand both concepts. However, I'm having trouble understanding Cross Validation as it pertains to Decision Trees. Essentially...
ImportError: No module named sklearn.cross_validation
Jun 5, 2015 · from sklearn.cross_validation import train_test_split This isn't ideal though because you're comparing package versions as strings, which usually works but doesn't always.
understanding fbprophet cross_validation - Stack Overflow
Nov 22, 2021 · 1 I was able to perform a cross validation to assess the models accuracy, but I am having trouble understanding the output. I have 687 rows, I want to train the model on all my data to …
Is there a rule-of-thumb for how to divide a dataset into training and ...
Assuming you have enough data to do proper held-out test data (rather than cross-validation), the following is an instructive way to get a handle on variances: Split your data into training and testing …
Cross Validation in Weka - Stack Overflow
May 4, 2012 · Then cross-validation is run. cross-validation involves creating (in this case) 10 new models with the training and testing on segments of the data as has been described. The key is the …
Cross validation in deep neural networks - Stack Overflow
Jun 10, 2017 · How do you perform cross-validation in a deep neural network? I know that to perform cross validation to will train it on all folds except one and test it on the excluded fold. Then do this for …
machine learning - Is k-folds cross validation a smarter idea than ...
May 24, 2022 · Should you be using k-fold cross validation? Compared to a single validation set, k-fold cross-validation avoids over-fitting hyperparameters to a fixed validation set and makes better use of …
What is the difference between cross-validation and grid search?
May 5, 2023 · Cross-validation is a method for robustly estimating test-set performance (generalization) of a model. Grid-search is a way to select the best of a family of models, parametrized by a grid of …
Evaluating Logistic regression with cross validation
Aug 26, 2016 · I would like to use cross validation to test/train my dataset and evaluate the performance of the logistic regression model on the entire dataset and not only on the test set (e.g. 25%). These co...
r - Cross validation for glm () models - Stack Overflow
I'm trying to do a 10-fold cross validation for some glm models that I have built earlier in R. I'm a little confused about the cv.glm() function in the boot package, although I've read a lot of help