# 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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### why do we have the "freedom" to set the gutter equations to +/-1 in SVM

Trying to understand SVM. I am sure that my reasoning can't be correct but I can't see what is wrong. We know that two points determine a line. I am trying to understand support vector machines using ...
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### Is There any Open Source Implementation of Large-Scale SVM?

Question: Is anyone aware of a publicly accessible python package for large scale SVMs? Thanks! Why the Question Ought to be Answerable: As has been noted (e.g., here), the SVM problem can be ...
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### 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 ...
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### Multiple kernel SVM is equal to one ANN - Is Kernel SVM better that one ANN?

I'm comparing multiple Kernel SVM with one neural network, e.g one ANN with one hidden layer. I have succesfully trained a neural network by using multiple Kernel ...
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### predict if news article belong to specific category or not?

I am still new to machine learning. I am trying to build an ML model to predict if an article belongs to a category or not. for example, I have three categories : [war, politics, and crime]. I choose ...
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### Dual of the SCM square hinge loss

Let $x_1,\dots,x_n\in \mathbb{R}^n$, $y_1,\dots,y_n\in \{-1,1\}$, $\lambda \ge 0$ and $K$ be the invertible Gram matrix $K=(x_i\cdot x_j)_{ij}$. Consider  (P) \qquad \qquad \min_{a\in \mathbb{R}^n} \...
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### Using a SVM to classify audio data

If I had 1000 audio files where three people are independently saying an animal at the same time, there can be 9 independent labels of animals. What features should I select from the audio file, and ...
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### SVM kernel for detecting if a substring appears in some given string

I'm trying to do the exercise in 16.1 in the book Understanding Machine Learning, Ben-David, et al. formulated as follows: Consider the task of learning to find a sequence of characters ("...
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### 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-...
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### Is SVM is a good choice for large dataset?

With my limited knowledge of SVM, I am following a tutorial on YouTube to create an End-to-End multi-class ML model . There the person is using SVM on a dataset with 9 images dataset, but the dataset ...
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### How to use HOG for object detection without using SVM?

I am following the tutorial to calculate the HOG feature matrix. However, it does not tell how to find the object using the HOG matrix. For example, I have an image of several pipes stacked together. ...
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### SVM: difference between soft and kernel technique

Most articles and textbooks say that soft margin SVM is used is the data is messy/not linearly separable. We introduce slack variables to make the data linearly separable. Kernels are used when the ...
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### Error in SVM classifier RBF kernel in MATLAB?

I had written MATLAB function for RBF kernel in SVM classification but I am getting the following error: Kernel function returns kernel product of incorrect size. ...
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### Model outputting repeated result in Flask back-end

I am trying to implement this working audio classification model into a Flask app for use on a website. However, anytime I upload an audio file, even one that was used on the test/training of the ...
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### An OCR model that can be easily improved on the user side

I am building OCR software, for this purpose I trained a model on many types of fonts, the model is SVM or NN but it is not ...
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### Is it ok to normalize data using minmaxscalar on dependent variable?

I'm trying to make a sales prediction using the column X = item_amount and y = item_price_total, I'm confused whether it's okay to normalize data on the dependent variable using minmaxscalar? With the ...
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### estimating coordinate correction

I'm working with 3d coordinate data (x,y,z), however I know that the z coordinate is systematically wrong and the error of z is dependant on both x and y. I however do have some data where I know the ...
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### Is SVM rotation invariant?

Let's say we have some data X and we want to find a linear separator using soft SVM with l2 regularization, and then we want to solve the same problem after applying some rotation matrix Q to the data ...
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### What is ROC curve based on for SVM?

I was studying about the ROC curves for Logistic regression. There is a threshold in this method that determines the classification. By changing this threshold we get different confusion matrices and ...
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### 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 ...
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### Is Linear kernel SVM always better than Logistic regression?

We know that linear kernel SVM may give better results than logistic regression since maximizing the margin usually leads to more stable results/better displacement of the decision boundary. But is ...
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### Is it sensible to use the ROC curve with an KNN model? And if so why?

I am a beginner doing my first ML project. I am doing a binary supervised classification on an unbalanced dataset and want to use the ROC curve as a performance metric of my models. I am using ...
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### 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 ...
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### Force positive coefficients for Logistic Regression and LinearSVC

Do you know what is the best way to force positive coefficients with Logistic Regression and Linear SVC using scikit learn? for instance ...
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### What input does SVM consider when doing the text classification?

I was using SVM for text classification pipe_lr1 = Pipeline(steps=[('cv',TfidfVectorizer()), ('lr_multi',MultiOutputClassifier(LinearSVC()))]) ...
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### How to get model equation/coefficients for SVM in Orange

I have dataset and want to train an SVM model, I have done so in Orange, and the model behaves good, I used the File -> SVM -> 'test and score' widgets, now I want to take that linear model and ...
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### How do I print data after fitting data into a pipeline?

I was using 3 functions form scipy: TFIDF vectorizer, Multioutput classifier and Linear SVC. The code goes like this. ...
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### SVM produces a constant accuracy when testing with development set, regardless of features

I am currently doing a class project to use a machine learning algorithm (SVM or Regression) to deduce whether two sentences are paraphrases of one another. We were given training, development, and ...
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### Is it possible to train a Support Vector Machine to a specific accuracy?

From my understanding, support vector machines run on the premise of minimizing some error function, usually with the goal of maximizing accuracy overall. However, there are a lot of contexts, ...
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### Can we train of a binary classifier with "A" to classify "a"?

I have a maybe naive question about the appropriateness of using binary classifications. This is a hypothetical example, so forgive me if it is too coarse. Let's say I want to train a support vector ...
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### 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?
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### Official page of Weka for SVM java code

I am using Weka to train a model from few days. I know Weka use Java code to implement a classifier. I also heard that Weka has some github pages to describe the java code for the classifiers. I like ...
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### Finding points in 3D space - SVM

In the SVM classification, we use planes to classify the labels points if the dataset has 3 input features. We need to use planes when input features are 3. I am describing a toy dataset with 3 input ...
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### Which line need to consider when try to separate two class given a feature set in SVM

Suppose I have a toy dataset like following ...
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### Proof of perpendicular distance of an observation from the Maximal Margin Hyperplane

I was reading about Maximal Margin Classifiers in "Introduction to Statistical Learning" and could not understand how is the perpendicular distance of an observation (which is a vector) from ...
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### working principle of Support Vector Machine

I have a dataset consisting of numerical features and categorical features. I want train the training set using SVM. SVM is a quadratic optimization algorithm. I would like to know the how SVM works ...
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### 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 ...
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### memory bound for kernel tricks in machine learning

Based on Andrew Ng's lecture on Kernel, you use training samples (referred as landmarks l) and use them during prediction to construct the higher dimensional representation of the given sample. This ...
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