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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Clustering by fitting many linear SVMs and clustering their weight vectors?

Let’s say I have a bunch of discrete sequence data, with each sequence belonging to some individual (there are ~1000 individuals and many more sequences). With a great deal of success, one can train a ...
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13 views

Lowering C parameter increases the number of support vectors

I know that the C (cost) parameter controls the trade-off between model complexity and misclassification. A large C should increase the error weight, and therefore the model complexity. Nevertheless, ...
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1answer
37 views

When using SVMs, why do I need to scale the features?

According to the documentation of the StandardScaler object in scikit-learn: For instance many elements used in the objective function of a learning algorithm (such as the RBF kernel of Support ...
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2answers
63 views

Machine Learning Methods for Binary Classification

I was hoping to get a nice list of alternatives to logistic regression and decision trees for binary classification ("Yes vs. No" or "Cured vs. Not cured"). I am more interested in identifying the ...
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2answers
18 views

What is “Verbose” in scikit-learn package of Python?

What is "Verbose" in scikit-learn package of Python? In some models like neural network and svm we can set it's value to true. This is the documentation: verbose ...
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1answer
45 views

How to simulate more data for machine learning?

I am attempting to analyze a small dataset using machine learning (SVM, binary problem). There are $103$ samples and $215$ variables (all variables are real numbers). Some of the variables (around ...
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14 views

SVM always predicts same label

I have 11 labels. I trained an SVM model: ...
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6 views

Is it possible to apply a weight against multiple attributes in Rattle?

Hi I'm trying to figure out how to apply weight to multiple attributes in Rattle. I'd basically like SVM or random forest models to give greater weighting to ...
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1answer
34 views

How to use SVM to do time series prediction?

I want to know how to use SVM to do time series prediction? what the differences of input vecvtor X of our model between time-series prediction and standard kernelized regression problem?
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11 views

Combining text and non-text features

I am working on a binary classification problem using SVM. I am currently using ksvm in R (kernlab package). The input is a combination of text and scores. I would like to be able to use substring ...
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33 views

Time series forecasting using SVM

I am trying to set up a Python code for forecasting a time series, using SVM libraries of scikit-learn. My data contains $X$ values at a day interval for the last one years, and I need to predict $y$ ...
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24 views

SVM doesn't work [closed]

i train a SVM with X=10X78 and two class but when i see the variable model, it's all 0 . ...
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0answers
10 views

Why are parameters in output of my support vector regression going to zero? [migrated]

I am trying to predict next value in a time series from epsilon-support vector regression using libsvm library in matlab.Following is my code. From an excel file, I am taking first 3500 samples for ...
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18 views

Suspicious Amount of Zeros in Confusion Matrix

I have a data set with about 45000 observations and three features. When I apply machine learning classification algorithms like naive Bayes, kNN and SVM I receive a lot of zeros in the resulting ...
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17 views

Should the number of normal samples always be more than that of anomalous samples in training set for anomaly detection?

I am trying to train an anomaly detection algorithm (one-class svm) on a data set with a few hundred positive samples and several thousands negative examples. Is it mandatory that I train the model ...
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1answer
54 views

Text analysis : What after term-document matrix?

I am trying to build predictive models from text data. I built document-term matrix from the text data (unigram and bigram) and built different types of models on that (like svm, random forest, ...
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3answers
289 views

How to intuitively explain what a kernel is?

Many machine learning classifiers (e.g. support vector machines) allow one to specify a kernel. What would be an intuitive way of explaining what a kernel is? One aspect I have been thinking of is ...
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18 views

machine learning for a ontology classification problem

I am working on a ontology based classification problem.The main objective was: computing ontology has keywords related to different categories.Each category talks about the domain it is related.For ...
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18 views

Why is linear svm solver faster than nonlinear solver?

Both linear and non linear SVM solve can be solved using primal or dual problem. Why is linear svm solver faster than nonlinear solver?
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9 views

Why am I getting an empty matrix from svmpredict? [migrated]

I want to make predictions from a simple time series. The observations y=[11,22,33,44,55,66,77,88,99,110] and at time ...
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34 views

How to report machine learning research?

I am using support vector machines and cross-validation for a binary classification task. I have constructed three different models, and therefore I have three sets of results. How should I report the ...
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46 views
+50

Combination of two SVM Kernels

According to the book "Support Vector Machines" from Cristianini and Shawe-Taylor, it is feasible to make kernels from kernels. My question is now more in application of this methods with tools like ...
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24 views

how can i find confusion matrix of svm classifier on MATLAB to classify into 4 types of HEART beat

i want to find confusion matrix of svm classifier. i am work on ECG signal to classify 4 types of arrhythmia using svm on MATLAB..i have write code for this but something is wrong plzz help me to find ...
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8 views

declare class label in classifier with only X field in r

I have a simple problem: I can do SVM classification with some packages but have problem with others. let's say: my data set for training= ds and for testing ...
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1answer
25 views

How to best sample for SVM and rpart in R's e1071 package?

I built a svm and a decision tree but I noticed that when I rerun the sample then the accuracy changes. This is obviously because the sample is changing every time. What is the best way to get the ...
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3answers
65 views

Criteria for classification performance

In binary classification, are there criteria or guidelines available to judge if classification performance of the testset (unseen data) is poor, medium or high? I realise that this may depend on ...
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20 views

Post-hoc analysis of variable selection

I am using support vector machines & 10-fold cross-validation for a binary classification task. For feature selection, I use the t-test. After doing the classification, I'd like to do a post-hoc ...
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18 views

Logistic regression performs better than SVM with poly kernel exponent = 2

I am running an experiment and I built a model initially using Logistic regression and later using SVM with poly kernel with exponent being 2. SVM model with exponent being 2 performs better than with ...
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1answer
74 views

Why am I getting 100% accuracy for SVM and Decision Tree (scikit)

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
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1answer
36 views

Choosing right range for data while using scikit-learn

I have a dataset with 1175 examples and 21 features which are in the range of [-1, +1], and two class labels 1 and 0. As I read in the most of the resources, it is good to have data in the range of ...
0
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2answers
46 views

Using k-means for reducing the size of the training set of a Kernel SVM

I have a classification problem with the following characteristics: a few million data points around one hundred features non-linearly separable Training a SVM with an RBF Kernel is not feasible ...
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2answers
25 views

Modelling for continuous dependent variable and discrete independent variables [closed]

Data - I have one continuous dependent variable and 10-15 factor independent variables. Tool - R What kind of models I can use other than linear regression and regression trees? I applied Linear ...
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1answer
20 views

Prove that a kernel is conditionally positive definite

A kernel is called positive definite (p.d) if its Gram matrix is p.d., i.e. all eigenvalues of the Gram matrix are positive for all possible input vectors in the feature space. My understanding of ...
0
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1answer
46 views

SVM parameter tuning for unbalanced classes (with class weights)

I am trying to run an SVM on an imbalanced dataset (0-90%, 1-10%) using the e1071 package, with the radial kernel. I am using cross-validation to select the best gamma and cost. Additionally, I want ...
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25 views

Most efficient SVM implementation

I'm currently using LIBLINEAR to perform linear SVM on a very large data set that sometimes collapses. Is there a more efficient implmentation of SVM? UPDATE: The C version of liblinear collapses, ...
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1answer
52 views

Is Support Vector Machine sensitive to the correlation between the attributes?

I would like to train an SVM to classify cases (TRUE/FALSE) based on 20 attributes. I know that some of those attributes are highly correlated. Therefore my question is: is SVM sensitive to the ...
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48 views

Obtaining a HOG feature vector for implementation in SVM in Python

I am new to sci-kit learn. I have viewed the online tutorials but they all seem to leverage existing data (e.g., digits, iris, etc). I need the information on how to process images so that they can ...
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23 views

set SVM parameter range values for tuning [duplicate]

I am newbie to using svm for classification. I want to tune svm parameters by .TrainAutofunction in EmguCV. But I don't know what are the range(min-max value) of below parameters that I should give to ...
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1answer
51 views

Training an SVM and performing cross validation

I am training an SVM and I have 40k Negative Samples and 17k Positive samples. What I did is that I have divided my samples into training and testing subsets. In order to train the SVM I have used ...
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6 views

R:svm predicts differently on trainigset

I want to use svm to predict the Sex using probabilities. The problem is that when I run part 2 several times, I get different results in the tab-matrix, although I do not change my parameters. What ...
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31 views

how to make or prepare range file in svm-scale in libsvm using matlab

Respected all, I am using LIBSVM, for scaling the input data svm scale function is used. The syntax is 'svm-scale -l -1 -u 1 -s range train > train.scale' or svm-scale -s scaling_parameters ...
0
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1answer
53 views

Logistic Regresion / SVM / Random Forest Implementation in Matlab

I would like to implement (L2-regularized) Logistic Regression, (L2 regularized) SVM and Random Forest for multiclass classification in Matlab (without using a toolbox or the corresponding functions ...
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1answer
20 views

Fit multidimensional feature into design matrix

I'm having trouble understanding how I can have a multidimensional feature in my design matrix. I understand the concepts of PCA, but I'd rather avoid it. I have the feeling that I'm missing out on ...
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14 views

support vector machine, classification, dummy variables in R

I am a bit confused about the converting of the categorical variables into dummy variables. Lets say I have a gender column, the values are female and male, and a disease column, saying what kind of ...
0
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1answer
28 views

Training data set size and SVM classifier

I want to do a multi-class classification of human action recognition. I plan to collect data. So, How can I estimate the minimum data set size. What are the important parameters?
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28 views

How is the mean area under the curve calculated?

I am using 10-fold cross-validation for performance estimation. From each of the ten iterations, I get an area under the curve (AUC) metric, e.g. ...
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22 views

Python: In which cases will random forest and SVM classifiers can produce high accuracy?

I am using Random Forest and SVM classifiers to do classification, and I have 18322 samples which are unbalanced in 9 classes (3667, 1060, 1267, 2103, 2174, 1495, 884, 1462, 4210). I use 10-fold CV ...
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0answers
23 views

Which one is correct phase for neural network or support vector machine? Features or Inputs?

Which one is correct phase for Neural Network or Support Vector Machine? Features or Inputs? Based on ...
2
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1answer
39 views

What is the chance level accuracy in unbalanced classification problems?

Suppose one has a balanced classification problem (50% of 0's and 50% of 1's). In such a case, the so called chance-level accuracy of classifier would be 50%. What is the chance-level accuracy if the ...
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How to create a multidimensional data structure in R as input to kernlab's ksvm()

This is a revision/rephrasing of my question originally posted on stackoverflow. How should I create the training/input dataset for a ksvm model with multi-dimensional input data? The process for ...