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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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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10 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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19 views

Time series forecasting use 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 for ...
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24 views

SVM doesn't work [on hold]

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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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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17 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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16 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
46 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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254 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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15 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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17 views

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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14 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
64 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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71 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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35 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 ...
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2answers
41 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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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 ...
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41 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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24 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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49 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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35 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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50 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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27 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 ...
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49 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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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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12 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 ...
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27 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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27 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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20 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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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 ...
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1answer
38 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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40 views

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 ...
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1answer
54 views

What are the best R packages for a classification problem with use of Neural networks [closed]

Surfing on the internet shows me that there are a lot of different packages and functions which can be used to train neural networks via R. packages such as 'RSNNS', 'nnet','neuralnet', etc. I'm ...
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22 views

Clustering data with one feature

Is there any built in method to cluster data with one categorical dimension in R? Basically, I have a data set including week of the year and if an event happened in that week. I wanted to use ...
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22 views

Confounding factor in cross-validation

I have been exploring a dataset using support vector machines. I am solving a binary classification problem and using stratified K-fold cross-validation for performance estimation (the SVM ...
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25 views

Semi-supervised learning vs supervised learning, what are the benefits and limitations?

Just wondering if any previous work compared semi-supervised learning vs supervised learning? Currently, I have got both datasets with and without labeling. And therefore, it is intuitive for me to ...
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1answer
41 views

Help for interpreting SVM cross-validation results

I am using support vector machines for an unbalanced binary problem (0: 25%, 1: 75%). I do K-fold cross-validation with $K=10$. The metrics I get are: 80% classification accuracy on average for the ...
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48 views

Predict out of sample values for support vector machine

I wonder how I can use the results for svm() in R for out of sample predictions. Assume that we split the dataset into train and test sets and use ...
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21 views

Class weights in unbalanced SVM classification

The answer to this question says that class weights for unbalanced SVM classification can be picked so that that sums of the weights for each class are equal. Should this be done before ...
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7 views

Is it possible to apply SVM on one dimensional dataset in R? [closed]

Is it possible to apply SVM on one dimensional dataset in R? if yes, please suggest me the procedure.