Tagged Questions
1
vote
1answer
30 views
Evaluating features and similarity measures
I am currently developing a classificator, which is supposed to classify into a number of classes. For this purpose I am
designing some features and similarity measures which I might use for a later ...
1
vote
0answers
19 views
Performance worse with new observations
I come from the computer science area but am new to machine learning / stats, so this question may be fundamental and easy.
I have time-series data (biological data), and, without getting into the ...
3
votes
1answer
122 views
Is it possible to compare two feature selections algorithms by cross-validations?
Assume I have two feature selection algorithms, A and B, which are developed based on SVM. I applied these two algorithms on the same dataset, a Liver Cancer dataset (400 features & 150 samples), ...
0
votes
0answers
45 views
Issues with sequential feature selection
I am trying to do some feature selection in gene expression data with 22215 features. I followed the tutorial here.
I initially applied filter method(ttest) to select the features having the best p ...
1
vote
1answer
144 views
Using Adaboost for feature selection?
Is it okay to use Adaboost to do feature selection (selecting a subset of dimensions $S$ from a high-dimensional feature vector $V$)?
I divided the samples into four non-overlapping sets: $A$ ...
0
votes
0answers
66 views
pathClass package R SVM-RFE
In several literature; its been published that Support Vector Machine performance can be enhanced if the features are carefully chosen. I am trying to do the same using R package "pathClass" using the ...
1
vote
1answer
140 views
How does scikit-learn perform $\chi^2$ feature selection on non-categorical features?
I'm experimenting with $\chi^2$ feature selection for some text classification tasks. I understand that $\chi^2$ test checks the dependencies B/T two categorical variables, so if we perform $\chi^2$ ...
2
votes
1answer
194 views
What is “feature space”?
What is the definition of "feature space"?
For example,
When reading about SVMs, I read about "mapping to feature space".
When reading about CART, I read about "partitioning to feature space".
I ...
1
vote
0answers
115 views
Kernel in PenalizedSVM R package
There is not option to select kernel in penalizedSVM R package. What kernel do they use?
Is there some other R package with penalized SVM methods where I can choose various kernels?
2
votes
0answers
71 views
Multiclass classification with SVM a question about the feature vectors
I was told I had to direct my machine learning questions to this site. So here it goes.
I'm trying to do Multiclass classification with SVM. I have 7 classes. Now I was wondering if the following is ...
3
votes
2answers
999 views
How does one interpret SVM feature weights?
I am trying to interpret the variable weights given by fitting a linear SVM.
(I'm using scikit-learn):
...
7
votes
4answers
395 views
Low classification accuracy, what to do next?
So, I'm a newbie in ML field and I try to do some classification. My goal is to predict the outcome of a sport event. I've gathered some historical data and now try to train a classifier.
I got around ...
0
votes
0answers
128 views
Feature selection for SVM and Maximum Entropy
In text classification problems where the number of features >> number of documents, is it useful to perform feature selection with filters (e.g. Information Gain) when using Naive Bayes. However, ...
12
votes
3answers
182 views
Is building a multiclass classifier better than several binary ones?
I need to classify URLs into categories. Say I have 15 categories that I'm planning to zero down every URL to.
Is a 15-way classifier better? Where I have 15 labels and generate features for each ...
4
votes
1answer
285 views
SVM for Image Segmentation?
I turn to this forum for advice with the following problem. If you could please shed some light on any aspect of this question I'd be very grateful.
Problem decription:
I'm trying to use an SVM to ...
1
vote
0answers
164 views
SVM importance of predictor variables
I am building a model in R using support vector machine (SVM) with KBF kernel.
The model seems to work quite well. I would like to assess the relative importance of predictor variables.
Can anyone ...
2
votes
1answer
277 views
How to select the final model with elastic net feature selection, cross validation and SVM?
I have a dataset of some 100 samples, each with >10,000 features, some of which highly correlated. Here's what I am doing currently.
Split the data set into three folds.
For each fold,
2.1 Run ...
2
votes
0answers
81 views
Non-linear (e.g. RBF kernel) SVM with SCAD penalties implementation
Is there one? I think there's a penalizedSVM package in R but it looks to use a linear kernel. Can't quite tell from the documentation. If it's linear, is there a R package that lets me calculate the ...
1
vote
1answer
330 views
The disadvantage of using F-score in feature selection
F-score can be used to measure the discrimination of two sets of real-numbers and can be used for feature selection. However, I once read that
A disadvantage of F-score is that it does not reveal ...
7
votes
3answers
2k views
Improving the SVM classification of diabetes
I am using SVM to predict diabetes. I am using the BRFSS data set for this purpose. The data set has the dimensions of $432607 \times 136$ and is skewed. The percentage of ...
15
votes
2answers
1k views
