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# Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

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### the role of basis functions in reinforcement learning

In the very simple examples of reinforcement learning (gridworld, mountain car), we use real numbers or some elementary functions as reward functions. When state spaces become larger and larger, and ...
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### Sparse vs compact representations

In sparse representations, we like to find representation of the input where most elements are nearly zero. On the other hand, in some applications we prefer dense representations such as word ...
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### How to mitigate the hierarchical error propagation in tree-structured classification

Suppose we have a multi-class classification problem, where the number of classes $K \geq 3$ We use a tree structure of multiple SVMs to divide and conquer the problem, with one example in the figure ...
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### How do I find multiple change points in an online dataset?

I am trying to develop a Python based script connected to a SQLite3 database to identify distinct system changepoints in an "online" datastream. Changepoint must be identified in less than 2 minutes ...
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### How to estimate a probability distribution

Suppose I want to estimate a probability distribution, is it common practice to simply fit a function to a frequency histogram? So in my work, I am training a classifier, the performance of which is ...
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### Does rank of observation matrix tell anything useful when applying machine learning?

Suppose I have an observation matrix of size $N \times M$ where $N$ is the number of samples and $M$ is the number of variables. If the rank of the observation matrix is $R<M$, does it tell ...
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### detecting circadian rhythm in a time series

I have a sensor that can detect minute changes in distance. It produces a time series. I would like to point it at people and detect things like their sleeping pattern. How would one build a system ...
625 views

### Anomaly detection in user behaviour using hidden Markov models

I would like to detect user anomalies or mal-behavior on a web site. For each user I monitor the web browser used, IP (and thus ISP & geo-location) of the user as well as users' activities on the ...
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### Using taxonomic levels as factors in random forests: does it make sense? Is it needed?

I want to test the effect of a set of predictors (ecological and morphological factors) on a categorical response variable (an animal behaviour). As far as I've read, random forests do not make ...
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### Efficient Portfolio Optimization Through Simulation

Apologies in advance for the (possibly?) poor terminology as I'm a bit of a novice in the field. I was torn whether to ask this on stackoverflow or here, so hope its the right place. Anyway, my ...
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### Adjusting the classification threshold of Naive Bayes

I've been involved in a machine learning project recently and am now in the process of writing the project up for a paper submission. We used the naive bayes classifier on the project and developed a ...
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### Formula for marginal probability in CRF++

On the website for CRF++ http://crfpp.sourceforge.net/ they mention that marginal probabilities can be output for each possible label. My question is, in CRF theory, what's the formula for this ...
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### Observation symbols for training a set of HMMs

If we are to classify 2 separate classes/actions using HMMs, we design 2 separate HMMs (one for each class). Do they share same set or a different set of observations-symbols for each of the HMM? If ...
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### Why would concatenating feature vectors lead to better estimates?

I wish to estimate the state of a system from two separate and disparate observations. A simple approach that I have seen in some literature is to combine the feature vectors (observations) by simply ...
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### Category selection for text classification

It is said that to achieve a good result (many different metrics) for text classification, it is not always a business of selecting the algorithm/classifier. Sometimes, it is even more important to ...