Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."

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Applying support vector regression to vector-valued functions?

So, just as a preface: this is my first time posting to this site, and I am also a machine learning beginner, so I apologize if my question is dumb or if I do something wrong, format-wise. Alright, ...
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8 views

Kernel function between time series of different lengths

I'm studying a data set composed of time series of different lengths; some are up to an order of magnitude longer than others. (If it matters, the data aren't actually temporally related; it's just ...
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got msg “convergence warning in initialization\n” running svmpath() [on hold]

I got msg "convergence warning in initialization\n" running svmpath(). Data consist of 15 factors, transformed by "model.matrix" into 84 constrasts; 4452 instances. ...
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8 views

In simple terms, what is a radial basis machine (RBM) modeling?

I stumbled on this term while trying to read this research article: http://clincancerres.aacrjournals.org/content/21/1/175 I don't have a background in statistics, so simple terms would be nice. Also,...
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15 views

Twitter Classification of tweets related to Ebola into 21 custom categories

I have a lot of twitter data (4GB) related to keyword Ebola. I want to classify the tweets into 21 categories. Categories :- Death - tweet is about death Health Care Workers - tweet is about ...
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11 views

How can you scale Gram matrix for SVM classification?

Why scaling is important for the linear SVM classification? gives a good intuition on why scaling is important when using SVM classification. There are two types of input when using SVM fit method : ...
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16 views

SVM: giving probabilities by sigmoid

For example, as for a binary classification problem, SVM usually gives a classifier rather than Probs. In other words, the SVM may gives us hyper-parameter, e.g., $W = [w0, w1, w2]$ for our data $X_{...
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18 views

Support Vector Classifier - Opposite Classification

I'm using a support vector machine (SVC from the SKLearn library in Python) to classify some time series data, aiming to predict the severity of injury to babies. A rough summary of the method is ...
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28 views

Ranking / Scoring: How to combine two classifiers into a single score?

Goal My goal is to build a ranking system based on three classes A, B and C. For the sake of the discussion, let say I am working with data about customers and their purchasing power. In my training ...
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2answers
69 views

Are linear classifiers (SVM, Logistic Regression) deterministic?

I am just starting to learn about classification and have been playing around with some linear classifiers. I was wondering if linear classifiers are deterministic--given the same model parameters and ...
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1answer
82 views

Comparing SVM Models using Different Methods for Data Generation

I have a set of SVM models that I am trying to compare. Each of the models is trained on a variation of the original data: The original data The original data using resampling scheme A The original ...
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23 views

SVM labeling more classes does not result in higher accuracy?

I used SVM to predict the ranking score of muffin recipes. X is a numpy array of ingredient amounts of a certain recipe and y is the label according to the online ranking score. First I labelled my ...
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21 views

Feature map of kernel

Let $K_1,K_2$ be valid kernels. Kernel $K_1$ has a feature map $Θ(x)∈R^{50}$ while Kernel $K_2$ corresponds to feature map $ψ(x)∈R^{10}$, satisfying: $∀i=1..10,∀x:ψ_i (x)=0.2 Θ_i (x)$ What is the ...
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37 views

Rank of kernel Gram matrix and classifier performance

In kernel machines we have some kernel function $k$ and we compute the $n \times n$ Gram matrix $K$ where $K_{ij} = k(x_i, x_j)$ for observations $x_i, x_j \in \mathbb R^p$. I'm letting $n$ denote the ...
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1answer
18 views

Same kernel for mixed/categorical data?

I know it's common practice, but is it right to apply the common kernels to categorical/mixed data? If not, are there alternatives? I'm expecting answers from both theoretical and practical points of ...
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15 views

Quadratic programming in SVM is inefficient in higher dimension?

I am learning SVM from this lecture - https://www.youtube.com/watch?v=eHsErlPJWUU - though I have some questions. Let's say we have d features: x1, x2, x3..., xd. And we have p sample: x1(1), x2(1), ...
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58 views

Find feature Importance not on basis of count but importance

I am developing a model for company users where there are multiple independent features which contributes to dependent feature userValue. I have generated 10k fake records programmatically and ...
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22 views

How can I overcome the “contrasts can be applied only to factors with 2 or more levels” when each factor has 1 level?

I have trained a model and now I want to predict the output for a new query with an svm. First, I got this error "length of 'center' must equal the number of columns of 'x'" which means that there ...
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20 views

Compute gradient for the SVM

I am working on Java implementation of the SVM. Suppose that I have the following loss function that needs to be minimized on weight-space: $$\frac{1}{N} \sum\limits_{i=1}^N \left(\frac{\lambda}{2}\...
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44 views

Should using SMO classification in WEKA take so long with large dataset?

I have a dataset of 205 features and 238000 samples. It is a combined dataset of several subjects' data that I want to use for between-subject classification. I am using WEKA 3.8 with a 64-bit JVM ...
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1answer
21 views

Combining two or more (SVC) models in Python/scikit.learn

I have some data which I use SVC models with 10 fold cross validation and a parameter grid search on (scikit.learn). I observed that the predictions of some folds have low accuracy, whereas remained ...
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27 views

Machine Learning: Non-Linear Regression over dataset with very similar predictors and very different targets

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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23 views

Machine Learning: How to solve “class imbalance” in Regression Algorithms?

I have a time-series dataset collected by a group of biologists counting the abundance of a particular animal species in an area. I later enriched this dataset with weather variables (e.g. temperature,...
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67 views

Measuring Accuracy of the SVM based model

I have developed a model which evaluates a user based on how important he is for the organization. For that purpose I have generated 1000 records for 1000 users. Here I have one dependent variable "...
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12 views

Obtaining exact output values of SMO based classification, before clearly demarcating them into classes

While running the SMO classifier in weka, if I have inputted my training labels as 0 and 5, (A binary set), then while running the classifier model on test data, are the outputs some decimal values ...
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24 views

What will be the input value (i.e. $x$ and $x′$) of RBF kernel for a given dataset or data matrix $x$?

If $x$ is a data matrix or dataset then What will be the input value (i.e. $x$ and $x'$) of RBF kernel $K_r(x,x')=\exp(-\frac{\|x-x'\|^2}{r})$ ? I can understand $x$ is same as dataset or data matrix ...
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1answer
29 views

R e1071 SVM always gives me (in average) below changes cross validation accuracy with random data

I am running e1071 linear SVM on my neuroimaging data. ( by function svm() ) When I was doing permutation tests, I found, in average, the cross validation (CV) accuracies with shuffle labels were ...
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14 views

How to calculate multi-class prediction probabilities using One vs All and One vs One classifiers

To be specific, let's consider Support Vector Machines. In the 1 vs all case, one has $n$ binary classifiers where $n$ is the number of classes. In each classifier one has two labels 0, 1 and for a ...
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14 views

Can binary svm have labels 1 and 26(any number but not 0,-1 or 2)? [duplicate]

I trained binary svm with lables 1 and 26. but while classification it returned a label of 1 and 2 which i have not mentioned during training. i thought it would return 1 or 26.
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65 views

Big difference of accuracy between C-SVC and nu-SVC using SVM

I'm currently dealing with an image classification problems. The objective is to classify the images to 4 classes, with 8000 images in the training set and 14000 images to predict. I'm using the SVM ...
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48 views

Normalise X/Y coordinates to stop jitter

Disclaimer: I am a programmer by trade, not a statistician, so please cater to my ignorance and I apologize now if I make any incorrect assumptions Please consider the following problem: I am using ...
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1answer
41 views

SVM training and testing error interpretation

I am new to machine learning and I just used SVM for the first time to analyze my dataset... Now I have created a figure that displays the training and testing error of the model as a function of ...
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19 views

The same input and different output form one-class SVM

I have applied scikit-learn OneClass SVM classifier to isolate the noisy tweets as outliers using one class training set. We use TfidfVectorizer class from sklearn to convert a collection of raw ...
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15 views

Reference request about feature maps in ML

Can someone kindly link to some recent papers on understanding feature maps in ML? It would help to get an idea of what are the recent issues there that people have been working on with regards to ...
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15 views

Building a hierarchical classifier

I'm trying to build a hierarchical classifier on R. I know my data has a tree structure with a root node + 3 levels and that each node on a level has 10 nodes coming out of it. ...
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1answer
32 views

How to justify the usage of “Radial Basis Function” as a kernel for SVM [duplicate]

I ran SVM with several kernels on my data. RBS has the best performing results. The task is similar to the text classification. I wonder how I can explain why RBS is actually the best kernel for my ...
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1answer
44 views

Why must kernel functions be scalar products [duplicate]

I'm currently reading Bishop's Pattern Recognition and Machine Learning. In the chapter on kernel methods, he's very clear that kernels must be "valid", that is: be representable as scalar products in ...
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30 views

How do you know that the assumptions of the model have been satisfied, and it’s ok to run the algorithm? [closed]

when using any simple algorithm like logistic regression, svm or even complex ones, how could you know that it’s ok to run the algorithm and use it in the industry? for example :when using logistic ...
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1answer
90 views

TOO low estimated SVM probability for most of the negative test examples?

I am using LIBSVM (as well as the fitcsvm and fitSVMPosterior of ...
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16 views

Labeling methylated/unmethylated sequences [closed]

I'm trying to do some test with matlab/SVM to classify methylated/unmethylated human sequences. I'm using these sequences freely avaible at this address: http://services.ibc.uni-stuttgart.de/name21/...
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40 views

Help interpreting formula for multi-class hinge loss

As I'm reading from wikipedia, and this Cross Validated question: Gradient for hinge loss multiclass, the gradient value for a training feature set is somewhat straightforward. However if I'm ...
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21 views

Is there a one-class hinge loss function?

Is there a [hinge] loss function that is suitable for one-class classifiers? i.e., anomaly detection. Thanks.
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61 views

How does gamma in SVM RBF kernel influence the accuracy?

I am working on a classification program using SVM RBF kernel. To find the best parameters C and gamma, I used grid search, and got the image below. What confuses me is that when gamma varies from 0.3 ...
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1answer
61 views

Using Random Forest Variable Importance to train SVM models (R)

I have trained a Random Forest model in R with the caret package but the results are not very promising. I have decided to try with SVM models but I have a great ...
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1answer
54 views

What is the right way to use SVM with cross validation?

I read a lots of discussions and articles and I am a bit confused on how to use SVM in the right way with cross-validation. If we consider 50 samples and 10 features describing them. First I split ...
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24 views

Learning with unbalanced classes

I have a biometric data set of size $n \sim 150,000$, with $p=21$ features $x_1,\dots,x_p$ representing information about people $-$ some categorical and some numerical. The original data set had only ...
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24 views

Unequal misclassification costs for SVC?

I wonder if there is a way to specify custom cost function in sklearn/python? (atm I use sklearn SVC) My real problem has 7 different classes, but to make it more clear lets assume that I want to ...
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How can I use gradient descent on the dual form of the linear SVM problem?

I understand that this is the dual form of the linear SVM problem (with a hard margin): $J(\mathbf{\alpha}) = \dfrac{1}{2}\sum\limits_{i=1}^{m}{ \sum\limits_{j=1}^{m}{ \alpha_i \alpha_j y_i y_j {\...
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9 views

How is the linear SVM's cost function derived from the Lagrangian (for the primal form)?

This is the cost function that seems to be used for training linear SVM classifiers: $J(\mathbf{w}, b) = \dfrac{1}{2} \mathbf{w}^T \cdot \mathbf{w} \quad + \quad C {\displaystyle \sum\limits_{i=1}^{m}...
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1answer
36 views

How does alpha relate to C in Scikit-Learn's SGDClassifier?

I'm trying to get the same linear SVM classifier model by using Scikit-Learn's SVC, LinearSVC and ...