# Tagged Questions

206 views

### How to use Gaussian mixture model for multivariate pattern classification

I am new to statistical pattern recognition and trying to learn.To begin with I am trying to work with two class problems and trying to classify motion activities as mentioned in the paper "Object ...
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For a probabilistic multi-class classifier we can get probabilities of membership of a new point $x$ to each class $y_i$; in case of 3 classes suppose that we get $P(y_a|x) > P(y_b|x) > ... 1answer 80 views ### How can we get the confidence (or probability) that a data-point belongs to an unknown class? Using any supervised classifier, we can usually get the probability that a data point$x$belongs to each class$y_i$, i.e.$P(y_i|x)$. However, in the case where the data-point x may belong to none ... 2answers 200 views ### Comparing 2 classifiers with unlimited training data I would like to compare 2 text classifiers C1 and C2, which can be trained with "unlimited" noisy training datasets, meaning that you can use as much data as you want for training, such data being ... 0answers 366 views ### Unsupervised anomaly detection with factor analysis (in R) The basic idea i'm trying is to model the data with factor analysis, assuming a latent variable structure that underlies the observations. Labels for "real" anomalies are available and used for ... 0answers 121 views ### Computation of Maximization probabilities of the EM algorithm I have implemented a semi-supervised Naive Bayes that makes use of the EM algorithm to iteratively learn from unlabeled data in a text classification problem, but I am not sure of the processing done ... 2answers 130 views ### Choosing which data-point to label (active learning) For an online unsupervised learning algorithm, data-points are learned sequentially. The performance may improve if in addition to the unlabelled data we have some labelled data-points (i.e. ... 0answers 148 views ### Computation of log-likelihood in semi-supervised naive bayes I have the following 2 questions about log-likelihood computation in semi-supervised Naive Bayes. I have read on several documents online that, in every EM iteration of the semi-supervised Naive ... 1answer 940 views ### K-means Mahalanobis vs Euclidean distance I currently am trying to cluster "types" of changes on bitemporal multispectral satellite images. I applied a thing called a mad transform to both images, 5000 x 5000 pixels x 5 bands. Each band is a ... 3answers 2k views ### Supervised clustering or classification? The second question is that I found in a discussion somewhere on the web talking about "supervised clustering", as far as I know, clustering is unsupervised, so what is exactly the meaning behind ... 1answer 265 views ### Getting probabilities over 1 in positive and unlabeled learning I have a question regarding PU-Learning, which deals with learning from positive-labeled (no labeled negative examples) and positive/negative-unlabeled data. Particularly, my question is about the ... 0answers 127 views ### Gaussian Mixture - Optimal number of components So, getting an "idea" of the optimal number of clusters in k-means is well documented. I found an article on doing this in gaussian mixtures, but not sure I am convinced by it, don't understand it ... 1answer 159 views ### K - means cluster always landing right on top of whole dataset mean I have a so so sized data set - 30 000 observations. I would like to run K-means on them but to restrict the center(mean) of the data. This is, I would like to push the clusters away from this mean. ... 2answers 241 views ### Can you use discriminant analysis to classify new observations into categories generated by a previous$k\$-means clustering?

After doing k-means clustering on a set of observations, I would like to construct a discriminant function so as to classify new observations into the categories I found after k-means. Is this at all ...
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### How to produce a pretty plot of the results of k-means cluster analysis?

I'm using R to do K-means clustering. I'm using 14 variables to run K-means What is a pretty way to plot the results of K-means? Are there any existing implementations? Does having 14 variables ...
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### Initializing K-means clustering

If I have a certain dataset, how smart would it be to initialize cluster centers using means of random samples of that dataset. For example, suppose I want 5 clusters. I take 5 random samples of say, ...
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### Market segmentation based on a time of consumption

I'm an almost graduated applied math student. I do some sporadic work in marketing. I have done a few market segmentation projects. I am soon going to do one which is important to me. I usually ...
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### Applying machine learning for DDoS filtering

In Stanford's Machine Learning course Andrew Ng mentioned applying ML in IT. Some time later when I got moderate size(about 20k bots) DDoS on our site I decided to fight against it using simple Neural ...