Questions tagged [hyperparameter-tuning]

Hyperparameter tuning (also called hyperparameter optimization) refers to the process of finding the optimal set of hyperparameters for a given machine learning algorithm.

Filter by
Sorted by
Tagged with
36
votes
6answers
8k views

How to set the number of neurons and layers in neural networks

I am a beginner to neural networks and have had trouble grasping two concepts: How does one decide the number of middle layers a given neural network have? 1 vs. 10 or whatever. How does one decide ...
17
votes
2answers
60k views

How to adjust the hyperparameters of MLP classifier to get more perfect performance

I am just getting touch with Multi-layer Perceptron. And, I got this accuracy when classifying the DEAP data with MLP. However, I have no idea how to adjust the hyperparameters for improving the ...
4
votes
1answer
181 views

New parameters in final training

I am training an Xgboost using 60% of my data and use 40% for testing. In the 60% of data, I use 5-fold validation to find the best number of trees. I find that the optimal number of trees is around ...
3
votes
2answers
261 views

High Recall but too low Precision result in imbalanced data

I was training a model using XGBoost Classifier on a heavy imbalanced database with 232:1 of binary class. Because my training data contains 750k rows and 320 features (after doing many feature ...
2
votes
2answers
145 views

Flask output not showing

I am trying to deploy a XGBClassifier model using flask. After giving the values to the relevant fields on the webpage, the ...
1
vote
2answers
536 views

Is a test set necessary after cross validation on training set?

I'd like to cite a paragraph from the book Hands On Machine Learning with Scikit Learn and TensorFlow by Aurelien Geron regarding evaluating on a final test set after hyperparameter tuning on the ...
1
vote
1answer
80 views

Hyperparameter tunning for Random Forest- choose the best max depth

I'm trying to choose the best parameters for random forest model. For that goal I hae run my model in loop with only one parameter and each time I have changed the number for the parameter max depth. ...
0
votes
2answers
80 views

Which hyperparameters of a neural network can be tunned independently?

The hyperparameter search is computationally expensive. I am wondering if one can tune the hyperparameters independently: tune one hyperparameter for a fixed value of other hyperparameters. For ...