3
votes
2answers
54 views

Assigning even partitions for Cross-Validation

This is a very basic question about cross-validation. Say that I have a sample size of 2901(or any difficult to divide number). How do I split this up into equal partitions (other than n=1)? And how ...
1
vote
2answers
118 views

High precision with low recall SVM

I'm classifying a data set using SVM and those are the precision and recall values for two classes. ...
1
vote
1answer
23 views

SVM Classification with Duplicate Training Instances

I'm using SVMs with linear kernel for sentence classification (binary). My dataset contains many duplicate instances i.e. many sentences in the training set have identical feature vectors. In the ...
1
vote
1answer
65 views

How do you validate your machine learning models?

I am wondering what approaches are commonly used for validating a classification or prediction models: Approaches that am using at the moment: Using truth-sets: - ROCs, Bootstrapping, Accuracy, ...
0
votes
1answer
31 views

Interpretation C value in linear SVM

My C value is very low (close to 0). Does this mean that my feature (dimensions) have no real separative (and thus predictive) value? (As the SVM basically chooses to ignore the training data ...
1
vote
1answer
55 views

Simple SVM Question

For a linear SVM, the documentation tells me the formula is: $$ \frac{1}{2}w^Tw+C\sum\limits_{i=1}^l\xi_i$$ Please explain to me in layman's terms what w (and ξ) represent. Is w the distance to the ...
0
votes
1answer
25 views

How to : a brief intro to scaling and rescaling data ( inputs) for supervised learning algorithms

I understand the concept of scaling and that it improves results in SVM's and NN's. however I would like to find somewhere where is is explained, in easy "layman's terms" terms. of how it is done. I ...
3
votes
2answers
33 views

What model would be appropriate for predicting electrical consumption given multiple (mostly) independent variables?

I have about 1000 samples worth of daily electrical consumption for a building. I'd like to build a predictor based on a number of observable inputs, including: daily temperature (continuous) hours ...
0
votes
0answers
29 views

Interpretation of Linear SVM Coefficients [duplicate]

I’m building a model using Linear SVM from the Scikit-learn package in Python. I have found that Linear SVM performs much better on my training set than Logistic Regression. My question is, is there ...
0
votes
0answers
11 views

How to interpret merits in Weka with ChiSquaredAttributeEval and SVMAttributeEval?

I want to interpret the goodness of attributes using feature selection with 10-fold cross validation. With ChiSquared I get something like this (deletet attributes with merrit was 0 in all folds): ...
0
votes
0answers
21 views

Predict feature combination with highest probability

I trained a Support Vector Machine with the caret package in R. My dataset looks the following: ...
0
votes
1answer
34 views

SVM cost parameter

In a SVM with linear kernel, could you explain to me what exactly the C parameter is/represents? An example why it's important to select a good value for C would also be appreciated. Thank you.
2
votes
0answers
41 views

Predicting the Success of a tweet

I want to predict the success of a tweet. In my case a tweet is successful when the sum of the number of favorites and the number of retweets is greater than 5. So my outcome value y is: y= ...
1
vote
1answer
56 views

Feature selection : how to select the Information Gain threshold?

I am trying to use Information Gain to select features when classifying text with a Support Vector Machine. For each word in our training data, we computed its information gain. Then, we should keep ...
0
votes
1answer
14 views

How to increase a particular terms's weightage?

I am doing Text classification using LibSVM in Rapid Miner. I am using TFIDF values for processing documents. I need to Increase weightage of some terms in the documents(for eg. words in BOLD and ...
1
vote
1answer
26 views

Why are linear SVMs used with HoG feature descriptors?

Ok, almost all applications I have seen that use HoG features use linear svm as classifier. Can someone explain for me why linear svm are chosen and why they give good performance? Are linear svm ...
0
votes
0answers
26 views

How to implement data I have to svmtrain() function in MATLAB?

I have to write a script using MATLAB which will classify my data. My data consists of 1051 web pages (rows) and 11000+ words (columns). The first 230 rows are about computer science course (to be ...
1
vote
1answer
48 views

Reverse AUC interpretation

Given a classifier (SVM) classifying in 2 'classes' (+1 or -1) for prediction purposes. It has an AUC score of 0.28, meaning its success rate is lower than just random predictions. If I just do the ...
0
votes
0answers
23 views

Cross validation and accuracy calculation in lib-linear

I have two questions related to cross validation in LIBLINEAR I have 1000 documents from which i take 300 documents for training and rest 700 for classification . I train 300 documents with ...
0
votes
0answers
10 views

In RVM, is the kernel allowed to depend on the full dataset?

I want to use Relevance Vector Machines and need to define my custom made kernel. I was wondering if it is allowed for the kernel to depend on the full dataset. For exampe, I can calculate a certain ...
0
votes
0answers
20 views

Sparse ELM vs SVM

What's the difference between SVM and Sparse Extreme Learning Machine with Gaussian kernel proposed in the following paper:http://www.ntu.edu.sg/home/egbhuang/pdf/Sparse-ELM-IEEE-T-Cybernetics.pdf As ...
1
vote
0answers
48 views
4
votes
2answers
104 views

Linear PCA versus Linear Kernel PCA

Sources and definitions: PCA: http://en.wikipedia.org/wiki/Principal_component_analysis KPCA: http://en.wikipedia.org/wiki/Kernel_principal_component_analysis My question: If in KPCA i choose a ...
1
vote
2answers
60 views

SVM parameter dependence on number of samples

I need to do a grid search to optimize SVM parameters gamma, C and epsilon (svm from e1071 r package). The problem is that I have a fairly large data set, about 100000 rows and 40 variables. I have ...
0
votes
0answers
25 views

$\nu$ SVM in terms of C-SVM

I have an implementation that solves the $C$-SVM optimization problem. Is it possible to use this algorithm to create a $\nu$-SVM? I know there is a connection saying $\nu$-SVM leads to $\rho ...
3
votes
1answer
72 views

Understand the reasons of using Kernel method in SVM

I understand that one can use kernel functions (i.e. radial kernel) to create non-linear decision boundary. However, there is something with my logic and I am sure there is something that I clearly ...
2
votes
1answer
20 views

SVM Training: Working Set Selection

This is related to Joachims's 1998 paper on training SVMs (link to paper). In 11.3, I understand how the term $V(\mathbf d)$ arises as a result of a first order approximation, and why it needs to be ...
0
votes
1answer
35 views

How is the training set constructed for multi-class SVMs?

Support vector machines do binary classification. If there is more than two classes, it is possible to train several classifiers instead of one. Two common approaches are training one vs. one (each ...
0
votes
0answers
46 views

R choosing the right classification approach for $ transaction volume categories

Our customers are Merchants and use our online payment service. Before they started using our service, they indicated how much $ transaction volume they will make per year. However this turned out to ...
0
votes
2answers
61 views

Explanation on One Class SVM

I was using One class SVM implemented in Scikit learn, Python for my research work. But I have no good understanding of this. Can anyone please give a simple, good explanation of One Class SVM? Thanks ...
1
vote
0answers
37 views

Testing classifier with binomial test when group sizes are unequal

I have data from 50 human subjects, who are divided into groups A and B (30 participants are in group A and 20 participants in group B). I also have a range of measurements from each subject. I have ...
0
votes
0answers
61 views

Set up a classification experiment via libsvm (MATLAB)

I would like to set up an experiment in MATLAB, to predict the class of a set of text instances in a two-class problem (e.g., the text talks/does not talk about ...
0
votes
0answers
43 views

3D space learning and prediction

I want suggestions about learning and predicting some object's position before hitting one out of four sides of a wall. I have some priority according to side of wall, and of course all the scenarios ...
3
votes
0answers
54 views

Vapniks proof of the basic lemma

In his book Statistical Learning Theory (1998), Vladimir Vapnik proves an inequality needed to prove a bound on the risk for indicator loss functions. Theorem 4.1 on page 133 he derives the following ...
0
votes
1answer
121 views

Choosing correct C and g parameters for libsvm

libsvm 3.18 Features: 10 I have used following, parameter range: ...
5
votes
3answers
204 views

What are alternatives of Gradient Descent?

Gradient Descent has a problem of getting stuck in Local Minima. We need to run gradient descent exponential times in order to find global minima. Can anybody tell me about any alternatives of ...
1
vote
1answer
76 views

One class classifier Cross validation

I am working on a problem which requires one-class classifier. I am using LIBSVM. I know there are tons of material out there but still I could not find the answer to my query. How do I estimate the ...
1
vote
1answer
73 views

Machine Learning Algorithm Confusion

I made a small application about cricket prediction using Machine Learning. I took records of 10 years (2001-2011) of ODI matches and prepared a training set. Now to predict a win or loss for a ...
0
votes
1answer
72 views

How to analyze plot from libsvm grid-search

I am trying to learn to use libsvm, I have used some defalut training sets to generate the plots by grid-search and obtained a plot below. I want to know, What type of plot is this, What does it ...
0
votes
1answer
52 views

Improving classification results

I have training data set with around 1500 positive set samples and 4500 negative set samples. All the features are numeric( floating or integer type values) and the data is specific to bio-informatics ...
0
votes
0answers
19 views

How the optimal separating Hyperplane can be constructed for a Support Vector Machine

i refer to http://www.markowetz.org/florian/FlorianMarkowetz_DiplMath_thesis.pdf on page 31-35 he tries to reformulate Vapniks proof that the primal an dual problem for the maximal margin hyperplane ...
0
votes
0answers
43 views

multi-class support vector machines vs machine learning

I am using SVM Type 1 with 4 classes and my classes have been defined manually. Is there any method or algorithm for automatically defining the class?
1
vote
1answer
59 views

Computational Complexity of Prediction using SVM and NN?

I've seen answers discussing the complexity of training SVMs and neural nets, but how about for predicting new responses once a model has been trained? For context, I'm working on an app that should ...
0
votes
0answers
38 views

Feature selection for one class SVM

I have around 300 features, i need to choose features for one class svm. can some one tell me the ideal algorithm for this use case. I know about that for feature selection regularised random ...
0
votes
1answer
32 views

decision boundary of support vector machine when data is not linearly separable

Screenshot from this video: This describes the decision boundary of support vector machine as a optimization problem with two constraints. But it seems to assume that the data points are linearly ...
2
votes
3answers
169 views

Does using a kernel function make the data linearly separable?

I'm reading about SVM and I learned that we use a kernel function so the data become linearly separable in the high dimensional (vector?) space. But then I also learned that they use the soft-margin ...
0
votes
0answers
32 views

Response surface of a particular discontinuous function

I have a function IR that depends on several (maybe 100) input random variables. I know ...
0
votes
1answer
38 views

SVM decision boundary conditions : derivation problem

I was trying to understand the derivation of SVM decision boundary. Suppose my decision boundary is y-x-1=0. Now in the book it was written that ...
0
votes
2answers
66 views

Software implementation of Support Vector Machines

I don't have a background of computer science, but i have my major in mathematics. I am interested in Support Vector Machines. I went through the theory as well as some practical examples. My problem ...