Questions tagged [tuning]
The tuning tag has no usage guidance.
11
questions
-1
votes
0answers
15 views
Is it possible to use multithreading for hyperparameter tuning with keras? [closed]
Since hyperparameter tuning seems to consist in training different models for the same task, I suppose it is a good idea to train them in parallel in order to gain some time. However, my attempt was ...
2
votes
2answers
37 views
Tuning hyperparameters never affects weights?
I am trying to better understand “tuning the hyperparameters”. I understand how to use GridSearchCV, I found the below explanation useful:
“As we do not know whether those parameters affect each other,...
0
votes
0answers
13 views
Best score in SVM
i am new to machine learning and i took the house price dataset from kaggle.com to learn and understand SVM.
for regression the best score would be 0.0 and for classification the
best score ...
0
votes
1answer
26 views
Perceptual Loss Layers Selection
I understand that in order to improve your generative model performance it is quite useful to compare your output and the target in the feature space, as stated in the paper Perceptual Losses for Real-...
1
vote
0answers
18 views
Is Hyperparameter Optimization A Discrete Or Continuous Problem?
I'm currently learning AI/machine-learning with Python and Scikit-learn. Not having a strong background in math, I'm confused on a certain point.
Say I want to tune the parameters of a machine ...
0
votes
1answer
38 views
how to do the hyper parameter tunning for one class svm in r programming?
x is input (single column)
tuned <- tune.svm(x=x, y =NULL, data=x,
type= 'one-classification',
tunecontrol = tune.control(sampling = "fix"))
For this I am ...
0
votes
0answers
15 views
Boosting Algorithm: What would happen if you omit the lambda (Make it equal 1 or make it too large) in this algorithm?
Taken from The Introduction to Statistical Learning textbook. I read the excerpt about boosting and have a fine conceptual understanding of the matter. Although I am curious why the learning parameter ...
0
votes
0answers
5 views
Caret for model performing and tuning paramter
I would like to ask, if I could use cross validation in caret for tuning parametr lambda and also for evaluating model performance. If I use savePredictions="final" and also I will tune parametr, it ...
0
votes
0answers
19 views
Tuning hyperparameters using sklearn GridSearchCV or validation_curve?
I'm working on tuning a classifier (so far just a decision tree) and running my classifier through both sklearn's GridSearchCV and validation_curve. Is either of these methods preferred and when would ...
0
votes
0answers
26 views
When tuning an SVM what are reasonable bounds for C and gamma when performing a gridsearch?
I am trying to tune the hyperparamters of an RBF-kernel SVM by utilizing a gridsearch strategy. I found different sources stating different ranges (2^-15, ... 2^15 or 10^-3,...10^3) all they have in ...
3
votes
1answer
28 views
Model tuning in the presence of incorrect training labels
I have a situation where I have a large amount of labeled data (~40 million records) with a binary outcome variable that has about 50% positive and 50% negative cases. The issue is that I know that ...
