1
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0answers
13 views

Feature boosting via rescaling in logistic regression and linear SVMs

If I were expressing a problem in terms of binary features, all encoded as {0,1}, could I boost some features by encoding them as {0,2}? Would the effect change based on whether I used either of the ...
1
vote
1answer
26 views

How to choose the training, cross-validation, and test set sizes for small sample-size data?

Assume I have a small sample size, e.g. N=100, and two classes. How should I choose the training, cross-validation, and test set sizes for machine learning? I would intuitively pick Training set ...
0
votes
1answer
16 views

Instance weighing in libsvm/liblinear

I often use the instance weights with Libsvm for classification problems. http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#weights_for_data_instances Does anyone know the details of the algorithm that ...
1
vote
0answers
32 views

SVM versus Bayesian regression example(s)?

I am trying to track down examples where some basic problems have been tackled via both classical Machine Learning algorithms and more formal statistical methods. In particular, I'm interested in ...
-1
votes
0answers
42 views

Sales Forecasting using Support Vector Machine

I have sales data for last three years 2011-2013. I want to use Support Vector Machine technique in R to do the predictions. I just wanted to know that the approach that I am using is correct or not? ...
1
vote
0answers
17 views

How do you deal with different distance based features?

If I have a model where the set of features where a cosign distance measure makes sense for some of the features, and a Euclidean distance measure makes sense for the others for example using a BOW ...
0
votes
0answers
16 views

Examine SVM result by plotting histogram of decision values of training samples

I'm working for object detection(computer vision) and have some problems in SVM training. My training configuration is as below. Balanced training set (positive 3998/ negative 3998) The dimension of ...
0
votes
0answers
20 views

Choosing fold size for highly Imbalanced dataset + nested CV + svm

I am trying to classify a dataset with ~1000 points. 90/10 is the class ratio - super imbalanced. Here are the following steps I did: Use 20 relevant features from previous knowledge Remove highly ...
0
votes
0answers
3 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
1
vote
0answers
19 views

How to give an input when you are using Machine Learning method in R

I am new to R and machine learning algorithms. I have basic knowledge of different machine learning algorithms. I have four years of daily sales data.I am trying to predict sales using Support Vector ...
0
votes
0answers
6 views

In LibSVM, svm-scale gives data that is all 1 and -1 [migrated]

As is described in the title, when I try to use svm-scale to scale my regression data into [-1, 1], the scaled data is all 1 or -1. I've confirmed that the original data itself has no problem. I'm on ...
0
votes
0answers
22 views

Prediction using Support Vector (SV) method in R

I came to know that using SVM method we can predict the future value more accurately than other normal methods (like ARIMA). My question is how do we give the future index value (let's say 101 when we ...
1
vote
1answer
67 views

Support Vector Machine Question

I need help with the following problem. I provided my current (partial) solution, and I hope someone can correct me and/or give me suggestions as to how I should solve the parts that I've left out. ...
3
votes
2answers
65 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
143 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
40 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
82 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
40 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
62 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
30 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
36 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
30 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
21 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
24 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
45 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
45 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
93 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
21 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
33 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
36 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
50 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
25 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
27 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
59 views
4
votes
2answers
128 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
81 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
33 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
85 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
23 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
38 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
50 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
43 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
84 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
45 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
55 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
145 views

Choosing correct C and g parameters for libsvm

libsvm 3.18 Features: 10 I have used following, parameter range: ...
5
votes
3answers
245 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 ...