Tagged Questions

3
votes
1answer
32 views

prequential evaluation - classification

I perform prequential evaluation like this: start with a training set, classify a number of examples, then add the correctly classified examples in the training set and continue to classifying the ...
0
votes
2answers
30 views

clustering gene expression data

I have a question about clustering. I' m managing gene expression microarray data and I would like to cluster them in classes. I searched around to find the best clustering algorithm for my data, ...
1
vote
1answer
50 views

Online logistic regression?

Here is my problem: I am developing an embedded system for some classification task. I am using Logistic Regression as my classifier. Now I train my classifier, and download my model on to my machine. ...
1
vote
0answers
24 views

Find exceptional parameters

I have been given an excel document with many rows full of numbers, some rows are marked. Each row represents a case in the clinic, each column represents a research test parameter. I need to find, ...
2
votes
0answers
36 views

SVM classifier (with soft-margin) implementation in R, gamma value and quadprog

I'm trying to implement a Support Vector Machine classifier in R and I have to solve the optimization problem using the quadprog R package which solves problems of the form : $$min_b \frac{1}{2} ...
2
votes
1answer
45 views

Compare classifiers based on AUROC or accuracy?

I have a binary classification problem and I experiment different classifiers on it: I want to compare the classifiers. which one is a better measure AUC or accuracy? And why? ...
2
votes
1answer
77 views

Recommend classification algorithms to try

I am working on a binary classification problem that is reasonably-sized (100k observations). I extracted 60 numerical features; the classes in the training set are well balanced. There are some ...
1
vote
1answer
29 views

Features selection using F-score for multiclass classification

I'm going to implement a feature selection algorithm, and I plan to use the F-score for because of its simplicity. The problem is that, the F-score is used for binary classification. How can it be ...
0
votes
1answer
47 views

regularized logistic regression and support vector machine

L2 regularized logistic regression differs with L2 regularized support vector machine with their loss function. Are there more deep differences for these two models? I tried several data sets, and ...
5
votes
2answers
81 views

Why do categorical predictor variables in regression need to be recoded as multiple predictors?

I'm learning about machine learning using Python's library scikit learn, and in their tutorial here they mentioned about a categorical variable color which can have ...
2
votes
3answers
191 views

Why is svm not so good as decision tree on the same data?

I am new to machine learning and try to use scikit-learn(sklearn) to deal with a classification problem. Both DecisionTree and SVM can train a classifier for this problem. I use ...
1
vote
2answers
60 views

Highly unbalanced test data set and balanced training data in classification

I have a training set with about 3000 positive instances and 3000 negative instances. But my test data set is pretty much un-balanced. The positive set only has 50 instances and negative has 1500 ...
0
votes
0answers
20 views

Relationship between vector dimesion and number of training samples for binary classifer

I have some general questions about binary classifers. Is there any relationship between sample vector dimesions and number of training samples for classifer? Is it good or bad to provide samples ...
1
vote
0answers
64 views

k-fold cross validation vs k times hold-out validation

I am facing the evaluation of a genetic programming algorithm. I am using the Proben1 cancer1 dataset to evaluate the models created by this algorithm. This dataset contains 699 samples, which is ...
0
votes
1answer
17 views

in nonlinear binary classification problems, which is the optimal dimension for make it lineary separable?

My question pertains to linear separability with hyperplanes in a support vector machine. Is posible to determinate the optimal dimension in which i have to transform a training data set for make it ...
-1
votes
0answers
23 views

kernels distances gram matrix classification

Could you please explain some thing about kernels? As I understand it is technique to map the feature space into a high dimensional feature space where we could separate two classes by a linear ...
1
vote
0answers
19 views

Tolerating labeling errors in classification

Suppose I have a set of labelled instances L, I apply a supervised learning (any classifier) on them to learn a model for classification. Now suppose that I want to add some new instances to L, but ...
3
votes
1answer
81 views

Which performance measure for unbalanced binary classification without an 'active' class?

My datasets have two classes A and B. The classes should be treated equally (there is no "active/inactive"). The datasets are unbalanced, sometimes A is more frequent, sometimes B is more frequent. ...
3
votes
1answer
70 views

PCA before train/test split

I have a dataset for which I have multiple sets of binary labels. For each set of labels, I train a classifier, evaluating it by cross-validation. I want to reduce dimensionality using PCA. My ...
4
votes
2answers
59 views

Binary Classifier with training data for one label only

In some real-life problems such as authentication, we only have training data for one label (x is authenticated) while the other label doesn't have any data or only few entries (x is an imposter). ...
2
votes
0answers
46 views

How should I distribute a classifier to customers?

When consulting, I often do my exploratory analysis and prototyping in R, and deliver results on the initial dataset to the client. The client wants to use the trained classifier in a production ...
0
votes
1answer
166 views

ROC curve and confusion matrix in classifier performance evaluation

I applied two different classifiers against the same validation set. It turns out that classifier A is better than classifier B in terms of ROC curve. However, classifier B is better than classifier ...
2
votes
1answer
141 views

Logistic regression as classifier and overfitting

I am using logistic regression to classify data into two classes. The variable to predict (Y) is either 0 or 1. I have found a rather good estimation of Y by logistic regression, and ended up using ...
0
votes
0answers
81 views

How to compute precision for a multiclass problem?

I have a question about calculating precision on a multiclass problem. If the true positives of some actual class is 0, and its false negatives is also 0, then how to calculate its recall? In this ...
0
votes
1answer
90 views

Choosing a better data-set

I have two data-sets for same samples. But they are produced using two different instruments. I want to choose one data-set for further analysis. How can I find/prove which data-set is better? To ...
0
votes
3answers
164 views

Binary classification machine learning

I have data set (30,000) mapping people to incomes(<=some number ,>some number) each instance has 15 features so as age, education. I would like some advice/pointers as to the best machine ...
1
vote
4answers
153 views

Neural networks for simplistic image classification

I want to train a neural network to classify a few simple, cartoony images like the ones below (for the moment I only have the classes house, tree, and sword). The images I am (currently) using ...
0
votes
0answers
23 views

Classifying foreground vs background for ellipse shapes

I have images of ellipse shapes which are read in as a matrix of pixel intensities. I'd like a way to be able to classify whether a pixel is foreground (belonging to ellipse) or background (not ...
4
votes
2answers
559 views

how to calculate precision and recall for multiclass classification using confusion matrix?

all, I wonder how to compute the precision and recall using confusion matrix for multi-class classification problem. In specific, one data can only be assigned with most probable class/label. I like ...
0
votes
0answers
53 views

Forming training set for Multinomial Naive Bayes

Is it true that Multinomial Naive Bayes requires equally by count training data for each class to get best performance? For example, we forming classifier for three classes - Japan, China, Korea. ...
2
votes
1answer
164 views

Simple text classifier: classification taking forever?

I work for a small tech startup, and I want to classify or users into demographics based on the domain of their email address. When users sign up to our site, they can enter a job category, or pick ...
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 ...
0
votes
0answers
80 views

Missing measure of variable importance for randomForest package in R [closed]

I have a problem with the importance measures given by the randomForest package in R. I pass the parameter importance=TRUE to my ...
1
vote
2answers
169 views

What is the name of this perceptron-like classifier?

I wanted to find a variant of the perceptron which works for non-separable data, so I tried using $f(x)=\mathrm{\tanh}(x)$ instead of the hard threshold function and finding a $w$ that minimises the ...
0
votes
1answer
102 views

How to create artificial data with one binary response variable?

I want to check various classification model like random forest, tree, knn,etc. I used some bench marking data set but now I need to simulate my own data set with a binary response variable.
1
vote
3answers
142 views

Classifying handwritten digits using PCA

Classify handwritten digits using PCA. Use 200 digits for the train phase and 20 for the test. I have no idea how PCA works as a classification method. I've learned to use it as a dimension ...
4
votes
2answers
170 views

Time series prediction with non-constant sampling interval

I have some data which can be modelled as such: each data sample $S$ is a series of discrete signal values $S(t_n) \in \{-1, 1\}$ measured at times $(t_{n, S})_{1 \leq n \leq N_S}$. The number of ...
3
votes
3answers
129 views

classifiers providing probability of being correct

The way I understand classifiers like kNN, ANN, SVM, Decision Trees... is that after being trained they will associate a new test object to one class out of a set of predefined classes. My question is ...
2
votes
2answers
90 views

Supervised learning algorithms for classification, that we should read first

What are the main supervised learning algorithms for classification (more than 2 classes), that we should learn first when we are beginners in that domain ? It is good if you can also give ...
0
votes
1answer
96 views

Learning a value of a parameter u given “true” or “false” prediction for each data-point x

We have a data-point x and many classes. Let $P(c|x)$ the probability that $x$ is of class $c$. We note $c_1$ the most probable class for $x$ (i.e. $P_1=P(c_1|x)$ is the highest probability), $c_2$ ...
2
votes
1answer
234 views

PCA before random forest classification

Does it make sense to do PCA before carrying out a Random Forest Classification? I'm dealing with high dimensional text data, and I want to do feature reduction to help avoid the curse of ...
0
votes
0answers
80 views

Mixing categorial and continuous data in Naive Bayes classifier using scikit-learn

I'm using scikit-learn in Python to develop a classification algorithm to predict gender of a certain customers. Amongst others I want to use the Naive Bayes classifier but my problem is that I have a ...
2
votes
2answers
112 views

Increasing the sample size does not help the classification performance

I am training a SVM classifier based on a given document collections. I started from using 500 documents for training, then I add another 500 for training, and so on. In other words, I have three ...
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?
2
votes
2answers
148 views

Importance of variables in logistic regression

I am probably dealing with a problem that has probably been solved a hundred times before, but I'm not sure where to find the answer. When using logistic regression, given many features $x_1,...,x_n$ ...
0
votes
0answers
51 views

Can RBMs be used for feature selection / reduction?

I have a data set that's ~ 150R X 2000C and was curious if an RBM is appropriate in situation with this type of imbalance. It's a microarray and I'm looking at a 0/1 classification problem. I'd be ...
2
votes
0answers
105 views

Good measures of feature selection and class separability in classification machine learning problems

An example of a good measure of class separability in linear discriminant learners is Fisher's linear discriminant ratio. Are there other useful metrics to determine if feature sets provide good class ...
2
votes
0answers
53 views

What are the most popular domain adaptation methods (for transfer learning)?

I understand supervised and unsupervised learning well, and would be able to identify some 'basic' examples of, for example, supervised classifcation as: SVMs Random Forests Logistic Regression ...
2
votes
0answers
61 views

Statistical comparisons of multiple classifiers performance?

If the accuracy of $classifier1$ is statistically significantly better than $classifier2$ as per some hypothesis test, and likewise the accuracy of $classifier2$ is statistically significantly better ...
1
vote
1answer
75 views

SVM optimization problem

I think I understand the main idea in support vector machines. Let us assume that we have two linear separable classes and want to apply SVMs. What SVM is doing is that it searches a hyperplane ...

1 2 3 4 5