Questions tagged [svm]
Support Vector Machines (SVM) are a popular supervised machine learning algorithm that can be used for classification or regression.
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SVC for Probability - Feature Selection
For typical models, we might be able to run a p-test to see which features have importance/should be removed. However, I'm not aware of any such tests for a SVC model.
In practice how should we ...
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SVC and Non Symmetric probabilities
I have a set of data, in which I'm attempting a binary classification. My metric to optimize is neg log loss. I've attempted multiple models using different classifiers particularly boosting, logistic ...
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Getting low accuracy while using QSVM
I am trying to predict weather using QSVM. The dataset I am using can be seen here :
Dataset: https://www.kaggle.com/datasets/muthuj7/weather-dataset
I am using ZZfeatyremap and Linear Quantum Kernel. ...
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Dimensions Issues while training and predicting output
I am trying to predict weather data using quantum svm algorithm. The code works fine till model prediction but the when I try to predict the output the following error arises.
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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 ...
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Regression model R2 drops when I remove outliers: is that even possible?
I'm analyzing how outliers in my dataset of size 8x8000 affect regression models. I have three scenarios: raw dataset (with outliers), Winsorized dataset (2% of the extreme outliers adjusted), and ...
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Is my SVR model doing the right thing?
I am doing wind forecasting modeling using SVR model and I wanted to compare the actual wind speed data and the predicted data.
I am not sure what I did wrong. I have pre-process the datasets and ...
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Why does SVM have a worse decision boundary than Logistic Regression?
I've run both SVM with Polynomial kernel with a degree of 3 and Logistic Regression with transformed features by PolynomialFeatures with the same degree of 3 on the default scikit-learn's Moons ...
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Does hinge loss penalize misclassifications beyond margin less than logistic loss?
This is a MCQ question I found
The hinge loss used in SVMs generally gives
less weight than logistic regression to points that are misclassified
with a high probability or score.
⋆ SOLUTION: True
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Binary Classification on a Medical dataset (SVM)
I am working on a project involving the usage of machine learning models to classify a given medical dataset. The dataset, wich you can find here: https://zenodo.org/records/10885957, contains 10.000 ...
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How to approach a classification problem when your dataset has many features?
I have a timeseries health dataset that I wish to classify, however I'm getting confused on how to classify it due to the high number of features.
I've followed tutorials on classification using SVM, ...
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Choosing Between Autoencoder with OC-SVM and Reconstruction Error for Anomaly Detection: Training Strategies and Considerations
I plan to use an autoencoder and One-class SVM (OC SVM) for anomaly detection.
So there are 2 strategies:
train the autoencoder, and use the encoder output (as reduced dimension) to train an OC SVM
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how is the feature mapping for the kernel trick "found"?
I did not find detailed explanations for this on wikipedia or other sites.
When I have a dataset that is not linearly separable and apply the "kernel trick" - how do I know if a mapping to ...
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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:
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Remove feature from kernel matrix
I am pretty new to machine learning so please bear with me :)
I am trying to do a binary classification task using an SVM with precomuted kernel (in python using sklearn).
I created my train kernel ...
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