Tagged Questions
0
votes
1answer
125 views
understanding of libsvm output
I applied libsvm to build a text classifier. The output looks like as follows:
...
0
votes
0answers
56 views
LIBSVM-based classifier assign very low score to positive validation files
Recently, I have been applying the LIBSVM to build a classifier based on a set of documents. The positive set has about 20000 files and negative set has about 50000 files. The built classifier is then ...
1
vote
1answer
146 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 $\chi^2$ ...
0
votes
0answers
53 views
the effects of feature matrix format on the training time of LIBSVM
I am using Libsvm to perform text classification tasks. I normally uses binary occurrence, TF/IDF to build feature set for the input documents. It normally takes quite longer for Libsvm to finish ...
1
vote
1answer
66 views
Relationship between number of training set and classification performance
Are there any research/paper on the relationship between the number of documents for training and the classification performance using support vector machine?
1
vote
0answers
140 views
Calibrating multiple binary SVM classifiers for one-vs-all multi-class classification
I'm classifying text using the one-vs-all approach. There are three classes. I've trained 3 different binary SVM classifiers using 10-fold cross-validation. The accuracy of the binary classifiers ...
0
votes
1answer
92 views
Regarding the feature generation method with SVM-based classification method
When using SVM to build classifier for a collection of documents, we can use term occurrence, term frequency or even TF/IDF. I would like to know what are the main disadvantages of using term ...
1
vote
1answer
107 views
The general approaches for improving a SVM-based classifier which is low precision and high recall
I built a SVM-based classifier against a data set, the precision is about 66% and the recall is about 88%. Generally, what are the options to tune the parameter that can increase the precision?
1
vote
1answer
99 views
Possible reason for failing to build a support vector machine
I was trying to build a classifier for a set of documents using a support vector machine. I choose to build the feature space using term occurrence. While experimenting, I found the following ...
5
votes
3answers
424 views
Support vector machine for text classification
I am currently having a data set, class 1 with about 8000 short text files and class 2 with about 3000 short text files. I applied LibSVM and tried a couple of parameter combinations in the ...
1
vote
0answers
32 views
Building document exemplar training models for SVM
What are the best methods for building document exemplar training sets for classification of unstructured data (documents and emails) using SVM? How do I optimize F-scores for these models when using ...
5
votes
2answers
955 views
Semi-supervised learning, active learning and deep learning for classification
Final edit with all resources updated:
For a project, I am applying machine learning algorithms for classification.
Challenge:
Quite limited labeled data and much more unlabeled data.
Goals:
...
1
vote
3answers
342 views
Text categorization/classification for small scale text
I'm looking into a way to classify/categorize sentences into pre-defined categories (around 10-15). Yes, indeed sentences, not articles or paragraphs.
Given the average length of articles are not too ...
15
votes
3answers
2k views
How well does R scale to text classification tasks?
I am trying to get upto speed with R. I eventually want to use R libraries for doing text classification. I was just wondering what people's experiences are with regard to R's scalability when it ...
