All Questions
Tagged with scikit-learnsvm
111 questions
1vote
0answers
40views
OneClassSVM super slow training with poly kernel
In contrast to questions like here, where a slow SVM training results from a high number of samples, I only have around 500 samples. Still, a single training fold (cross-validation) takes several ...
1vote
1answer
41views
Unexpected behaviour of Scikit-Learn SVR
I'm using Scikit-learn to fit a support vector regression on a really simple dataset of car stopping distances vs car speed. My code for applying SVR to this dataset is: ...
- 113
0votes
1answer
76views
1vote
0answers
33views
How does ROC work with SVM?
Could someone please explain how ROC works with SVM? Specifically i'm using RocCurveDisplay.from_predictions(y_test, y_pred, ax=ax[1]) which works fine. Since the ...
1vote
2answers
299views
Does it make sense to tune a model in scikit-learn and copy/paste the parameters into Rust's linfa?
I have a situation where my data can only be read from in a hosted Python environment, due to data security reasons. However, I am constrained to run ML models in a Rust environment due to work-...
- 111
0votes
0answers
87views
Issues with sklearn.svm.SVC
I am trying to use the sklearn.svm.SVC on a relatively big dataset, 1.5k test/train samples, 512 features each, one sample per class (so, 1.5k classes). I know that SVC doesn't scale well, so at first ...
1vote
0answers
16views
Boosting the effect of some of the features in SVM
I'm doing text classification with SVM. I'm using Tfidf vectorization. In addition to the text vectors, I have a context data denoting the possible outcomes of the prediction. For example, I have a ...
- 121
2votes
2answers
3kviews
Grid_search (RandomizedSearchCV) extremely slow with SVM (SVC)
I'm testing hyperparameters for an SVM, however, when I resort to Gridsearch or RandomizedSearchCV, I haven't been able to get a resolution, because the processing time is exceeding hours. My dataset ...
0votes
1answer
43views
what happens when test data has an instance on the hyperplane. How SVC() classifies it?
What happens when test data has an instance on the hyperplane? How does SVC() of scikit-learn classify it?
- 35
2votes
0answers
81views
Feature selection and model performance
Featuretools provides an automated way to generate features from your data, by providing relationships within your data and applying their so-called deep feature synthesis. It generates features like ...
- 121
2votes
0answers
666views
random_state on train_test_split() appears to have large effect in performance metrics?
To summarize the problem: I have a data set with ~1450 samples, 19 features and a binary outcome where classes are fairly balanced (0.51 to 0.49). I split the data into a train set and a test set ...
- 31
3votes
1answer
448views
How do I use wavelet transform for feature extraction correctly?
I'm trying to classify words based on EMG signals using a support vector machine as my model. My dataset includes 15 classes (words) with 230 repetitions and 1000 features each. I already merged all ...
- 31
2votes
1answer
2kviews
Imbalanced data set with Sample weighting - How to interpret the performance metrics?
Consider a binary classification scenario whereby the True class (5%) is severely outbalanced to the False class (95%). My data set contains numeric data. I am using SKLearn and trying some different ...
6votes
2answers
379views
How sklearn SVM find the initial hyperplane before Optimisation?
The optimization goal of the SVM is to maximize the distance between the positive and negative hyperplanes. But before optimizing, how does sklearn first find the positive and negative support vectors ...
- 261
1vote
0answers
58views
How to handle unclassifiable data in the dataset
Premise: Classification problem Input is three text fields Output classes are A, B, A&B (Note: A and B are not always exclusive though usually are, hence the 'A&B' class) Sci-Kit Learn is the ...
