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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11 views
Combine AdaBoost and Support Vector Regression?
I have read several papers about using SVM instead of decision tree in AdaBoost, but I haven't seen any papers about using support vector regression (SVR) in AdaBoost. However, if using support vector ...
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3answers
121 views
Looking for a classification (?) algorithm for linearly separable but unlabeled data points
I have a dataset that is linearly separable with two lines - something like that:
Now I'am looking for the right kind of algorithm to do what I guess a SVM would do with labeled data - find the ...
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0answers
28 views
New images always predict one label
I have trained a SVM for image classification using RGB histogram as features and a couple of other ones.
These are my feature and label sizes:
...
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1answer
28 views
Having averaged trials which are less than the number of features
Suppose I have an experiment where I have 70 features and 48 samples. The target variable is binary (0,1) and the 48 samples are divided such that 24 of them correspond to outcome 1 and the other 24 ...
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3answers
48 views
Why did Logistic regression perform better than svm? [closed]
I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G].
I have tried different ML algorithms and found that Logistic regression out ...
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1answer
32 views
Tuning C hyper parameter in Soft Margin SVM in Matlab
How to tune the C 'BoxConstraint' hyperparameter in soft margin SVM to get the best optimal value?
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13 views
Hard margin SVM in Matlab
How can I build a hard margin svm model using matlab builtin functions such as fitcsvm and fitclinear? Should I set the ...
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0answers
24 views
SVM hard and soft margins in matlab,
I am comparing the performances of several SVM models in matlab using the fitcsvm function,
and I want to double check that I am using the correct syntax
for hard ...
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0answers
31 views
SVM hyperparameters using Matlab's fitcsvm and OptimizeHyperparameters
I am building SVM models and will compare their performances, linear vs RBF,
and I'm using OptimizeHyperparameters to get best hyperparameters C (BoxConstraints)
...
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1answer
74 views
3
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1answer
32 views
An ambiguity in SVM equations about misclassified data
I have encountered an ambiguity in SVM equations.
As is stated in Chris Bishop's machine learning book, the optimization goal in SVM is to maximize this function:
$$C\sum\limits_{n = 1}^N {{\xi _n}} ...
2
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2answers
63 views
Setting best SVM hyper parameters
I have a non linear data set, and I am using SVM (RBF kernel) to build a classification model, but not sure how to set the best hyperparameters of the SVM, C and gamma in Matlab ...
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1answer
37 views
Implementing SVM from scratch?
I am trying to implement the rbf kernel for SVM from scratch as practice for my coming interviews. I attempted to use cvxopt to solve the optimization problem. However, when I compute the accuracy and ...
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1answer
15 views
When to question output of model
I'm unsure of how to ask a question without making it seem like a code review question. At what point does one question whether they've actually implemented the algorithm and-or model correctly? ...
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1answer
16 views
What is the possible range of SVR parameters range?
I'm working on a regression problem. While tunning the Parameters of SVR I got the following values c=100, gamma= 10 and epsilon =100. For which I got 95 percent r-square. My question is what is the ...
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0answers
15 views
Hyperparameter Tuning with Simulated Data
I'm trying to create a SVM classifier which can predict some fault, and to train it I'm using simulated examples of the fault. Of course, the simulations are not perfect, but they appear to be good ...
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3answers
43 views
Are support vector machines and logistic regression equivalent if data is linearly separable?
I understand that SVMs separate data drawing an hyperplane with the biggest margin, but doesn't logistic regression do the same thing if data is linearly separable?
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3answers
56 views
How to set hyperparameters in SVM classification
I am studying image classification using SVMs and it is generally defined as so...
N = number of training examples
W = is the weights
f(x, W) = dot product
λ is explained to be set through cross-...
2
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1answer
31 views
Dataset where svm performance is significantly different from random forest
Is there a specific dataset where svm performs significantly better or worse than random forest?
I know that the performance could depend on the dataset but is there a specific dataset?
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0answers
23 views
Improve precision of binary classification - SVM in Matlab
I'm using linear SVM for binary classification. The classes were imbalanced so I decided to under-sample the majority class. I have 34 features and the data includes 2000 observations. I think now ...
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0answers
45 views
When to use SVR over other regression models
I am confused about when to use Support Vector Regression over other models like Random Forest Regression and XGBoost. I expected XGBoost to give the best prediction score(r2_score) for my regression ...
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0answers
9 views
One vs one SVM for classes 1 and 5 but I have 10 classes in total. Should I train and test on all rows or should I subset?
I want to use soft margin SVM for my dataset. My dataset contains 10 digits - 0 to 9.
I need to train using one-vs-one SVM classifier(one digit is class +1 and another digit is class -1) for digits '...
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1answer
51 views
How to convert binary classifier to multiclass classifier?
I am a biggener student in Machine learning, and I want to ask if is it possible to convert a binary classifier label (y) by applying some condition on column1 to get a third situation.
I.e. ...
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1answer
59 views
How do I create a feature vector for the training of an SVM?
I have an understanding problem with implementing an SVM as a classifier for images.
The whole thing should be done in python.
Now, when I have extracted all the features, e.g. HOG, contours, textures,...
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2answers
39 views
SVM radial basis generate equation for hyperplane
I would be very grateful if I could receive some help regarding generating hyperplane equation. I need to generate an equation for hyperplane, I have two independent variables and one binary dependent ...
2
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1answer
33 views
Is splitting the data set into train and validation applicable in unsupervised learning?
I am having a tough time implementing all the steps of setting up support vector machine (SVM) for unsupervised learning. My data set is labelled but for educational purposes I am learning ...
2
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2answers
57 views
MAE,MSE and MAPE aren't comparable?
I'm a newbie in data science. I'm working on a regression problem. I'm getting 2.5 MAPE. 400 MAE 437000 MSE. As my MAPE is quite low but why I'm getting high MSE and MAE? This is the link to my data
...
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1answer
36 views
Support Vector Machine Errors
What is the difference between SVM classification error, SVM margin error, and SVM total error ? Is there any clear definition for them ? And what is C parameter in SVM ? Its totally confusing me !!!
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1answer
64 views
Scaling does not speed up the SVM model
I tried to standardize the training data with samples of 629,145 rows and 24 features:
...
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1answer
82 views
Why am I getting very different results between SVC, LinearSVC and Naive Bayes?
I am doing classification by using bag-of-words model. The goal is to locate users based on their tweets. Splitted the data as 80% training and 20% test.
I did experiments with sklearn's SVC and ...
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0answers
6 views
General way of constructing adjacency matrix in Laplacian SVM semi-supervised technique
I am trying to implement a Laplacian SVM classifier (trained in primal) using algorithm from this paper.
I would like to know what is the most common way of constructing adjacency matrix and the most ...
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0answers
18 views
How to choose the support vectors after minimizing the objective function?
I'm training a SVM that uses the following objective function:
$$
\frac{1}{2}\sum_i{\sum_j{\alpha_i\alpha_j t_i t_j \mathcal{K}(\vec{x_i}, \vec{x_j})}} - \sum_i{\alpha_i}
$$
The objective function ...
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0answers
26 views
what is fuzzy svm?
I have to solve this question for my homework but I don't get how to formulate svm to FSVM. can someone please guide me?
What is your idea to have a model of SVM classifier in which instances can ...
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0answers
16 views
SVM Cost function change to improve its computational efficiency
While listening to Andrew Ng's course of Machine Learning he said that the
SVM's cost function term $\frac{\Theta^T\Theta}{2}$ is usually changed to $\frac{\Theta^TM\Theta}{2}$, where matrix $M$ ...
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4answers
161 views
Is the prediction algorithm absolutely the same for all linear classifiers?
Is the prediction algorithm absolutely the same for all linear classifiers and linear regression algorithms?
As known, any linear classifier can be described as: ...
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1answer
106 views
How to feed data to Machine Learning Model?
I'm working on an SVM model as my college project. And the goal is to identify whether a tumor is benign or malignant. I'm implementing the model in Python. I found the data set from Gene Expression ...
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1answer
85 views
Scaling label encoded values for Linear Algorithms
I have encoded categorical variables to numerical values. As we know that for feeding values to Linear Algorithms like SVM or KNN, we scale the values for columns having large variations.
I have ...
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1answer
23 views
RBF kernel can classify two classes as in figure?
As you can see, I have some points (belonging to red and blue class), and I would to use an RBF kernel but I think that an RBF kernel can make points linearly separable only if they are located in ...
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1answer
68 views
test accuracy of text classification is too less
I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G].I have 13 examples for each class.
I preprocessed the subtitles in the following ...
2
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1answer
78 views
SVM vs RVM, when to use what?
I'm currently working on a project where I'm supposed to compare the efficiency of SVM vs RVM, there seems to be a lot of information to be gathered about RVM whereas I find rather old documents about ...
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0answers
31 views
Structured Support Vector Machine (Joint Feature Map)
I'm studying Structured Support Vector Machine. (https://en.wikipedia.org/wiki/Structured_support_vector_machine)
The theory's clear, but I need a tangible example to make everything more concrete.
...
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1answer
20 views
Context classification problem
I have a bunch of articles about science from a certain website. When a new article is published, I want to determine if that article is really talking about science (and not politics for example). ...
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1answer
40 views
Example of a problem with structured output labels
I'm studying SSVM (Structured SVMs).
On my book is stated that Structured SVM is an extension of the SVM, in which
Each sample is assigned to a structured output label z ∈ K, e.g. partitions,
...
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0answers
26 views
I have data of some movies and their subtitles.I want to classify them based on their ratings
I will convert the subtitles into vectors and use them as features to classify the movies into different categories based on their ratings.The problem that I am facing is my feature vector is much ...
2
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0answers
22 views
solution of quadratic optimization in support vector machines
In support vector machines, the minimization problem with inequality constraints can be converted to a minimization problem of Lagrange multipliers with equality constraints by KKT condition and ...
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0answers
19 views
Are there any good solutions for putting a radial basis kernel support vector machine into production?
Are there any good options for a radial basis kernel SVM where I can serialize the model to store and later deserialize and evaluate? I'm using H2O for some other things and it supports SVM but no ...
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1answer
40 views
What exactly is .csv in machine learning? [closed]
I already have dataset of dogs and cats , so do i need to make .csv file or can i directly use the dataset for classification
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1answer
23 views
How to break down large SVM classification model?
I have a classification problem with large number of classes: feature set is 512 Dimension, number of classes are around 3000. This is a face identification problem. (identify among 3000 celebrities, ...
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2answers
46 views
Poor performance for unbalanced dataset
Consider a dataset A which has examples for training in a binary classification problem. I have used SVM and applied the weighted method (in MATLAB) since the ...
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1answer
40 views
svm optimization problem
Suppose we have the dataset:
{(3,1),(3-1),(6,1),(6,-1)} {(1,0),(0,1),(0,-1),(-1,0)}
the first set represent the positive label, and de second the negative.
I want manually find the support vectors, ...
