Refers to techniques for classifying data into categories based on similarities (which can either be known previously, or learned).

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Clusteriod questions

I would like to clear some things up because I'm confusing everything. A $clusteriod$ is a coordinate for the mean value of a cluster? So if I have a 2-d .csv file I wish to perform kmeans, the ...
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4 views

EM/K-means task at hand/confusing

Hello I am getting into machine learning and patter recognition, however it's still quite a jungle at the moment. I am using WEKA and Java to try and create my first program. The following is what ...
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13 views

Algorithms for invariant image recognition

I am interested in the current state of affairs when it comes to image recognition. I am particularly interested in algorithms that can handle a high degree of invariance. Except for Artificial ...
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14 views

Identification of a tagged person on photo

I'm not sure if this problem was discussed before - if so could anyone please provide the link. The problem is the following: let's say I have a photo with some person who is tagged there, in the same ...
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12 views

Can KNN theoretically be less accurate than pattern averaging?

My task is pattern recognition. I need to classify 2D matrices into an arbitrary number of classes. The question is: For pattern classification, could k nearest neighbours algorithm ever be less ...
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26 views

Investigate correlation between one variable and combinations of others

We're conducting a study which correlate the incidence of various conditions during pregnancy and in newborns and the use of artificial reproduction technique (ART). This way we saw that some ...
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33 views

Proof that a density proportional to Gaussian is Gaussian [duplicate]

I try to develop Bayesian estimation for one dimensional Gaussian with unknown $\mu$ and known $\sigma$. I got \begin{align} p(x|D) &= \int p(x|\mu)p(\mu|D) d\mu \\ &=\int ...
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11 views

Hopfield Neural Network only for Content Addressable Memories?

I'm beggining to study some Neural Networks and i just came across Hopfield model. I'm a little puzzled about its use: is it only "limited" to content adressable memories? is content adressable memory ...
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33 views

Improving dynamic time warping word recognition system

I recently got interested in speech recognition and have implemented a simple dynamic time warp system for word recognition for my own learning purpose. However after testing a bit I believe that I ...
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15 views

What are the states and observation in HMM speech recognition?

For example: Given a two state HMM a and b If I define a -> b = # a -> a = # b -> b = # b -> a = # Pr(A|a) = # Pr(A|b) = # Pr(B|a) = # Pr(B|b) = # ...
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27 views

How is 'memory' implemented in Neural Networks?

I looked around into various articles on NN. I cant seems to grasp a basic idea - how a NN would remember what it has learnt? For example lets say there is a NN which was trained to recognize a ...
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15 views

Neural Networks. General approach to predict nearest future value (recognise incomplete pattern)

I need a general idea (and learn a bit of terminology as well) on how to approach the following problem: I have data coming in real-time but in uniform intervals (1s). each portion can have 1 or ...
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1answer
37 views

How many features can we use to avoid overfitting the classification?

We have a classification problem: classify type A tumour from type B tumour. In total we have 50 patient cases (25 A and 25 B cases). We use texture or shape analysis to generate features we can ...
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34 views

Machine learning : learn feature value range for a classification

Which domain the problem belongs to? Given a set of products some are classified as cheap and some not. The task is to determine the price range (probablistic) for cheap products ? Supervised ...
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2answers
36 views

Choosing the number of principal components to retain before training a neural network for classification

I am working on neural networks and I am currently creating a perceptron that will work as a classifier for a data set of images with faces. I am required to perform pca (principal component analysis) ...
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24 views

Finding genuine arrears and default arrears from rent payment patterns

I am currently working on some housing data - in particular analyzing the tenants' rent payment information and I am stuck on progressing with the following: I have to classify tenants based on their ...
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2answers
57 views

Mining patterns in continuous sequence

I have data in form of $N$ sequences $s_j=(t_i, e_i)_{i\in\{1,\ldots,n_j\}}$ with $n_j$ data-points each, where $t_i$ is a time-stamp and $e_i$ is a categorial event, say $e_i\in\{A,B,C,D\}$. The $N$ ...
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571 views

How to understand “nonlinear” as in “nonlinear dimensionality reduction”?

I am trying to understand the differences between the linear dimensionality reduction methods (e.g., PCA) and the nonlinear ones (e.g., Isomap). I cannot quite understand what the (non)linearity ...
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5 views

Using Quality metrics of BIRCH Clusters

What is significance of quality metrics of BIRCH Clusters Distance3 and Distance4. Appreciate if there are pointers are how to use Average Intra Cluster Distance (D3) and Average Inter Cluster ...
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10 views

Testing Cluster Assignment/Pattern Matching against BIRCH Clusters

I have a dataset of size >35K in size / >50 dimensions. Used BIRCH algorithm for clustering. While testing, the data points with which cluster formed is not matching i.e., The data point shows closer ...
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31 views

Pattern recognition in state sequences

I have a sequence of states of a system. Each state is defined by an abstract identifier e.g "Eating", "Sleeping" etc... and a duration. So a state is basically ...
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2answers
62 views

Clustering a long list of strings (words) into similarity groups

I have the following problem at hand: I have a very long list of words, possibly names, surnames, etc. I need to cluster this word list, such that similar words, for example words with similar edit ...
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38 views

How we can add new data in training time of neural network without stopping it in MATLAB?

I have a binary classification problem. Now I'm using patternnet in MATLAB R2014b to design a neural network for this problem. ...
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8 views

Characterizing “typical behavior” for events?

I need to build a model to characterize what is typical for a series of events, which in turn will be used to flag atypical events. As an example, think of credit card purchases (how often? what ...
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28 views

why pretraining for convolutional neural networks

Usually Back propagation NN has the problem of vanishing gradients. I found that Convolutional NN (CNN) some how get rid of this vanishing gradient problems (why?). Also in some papers some ...
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50 views

Change in objective function optimization - Regularization in Logistic Regression

If I have the objective function of Logistic Regression to optimize by maximizing it, would it change to a minimization problem when I add regularization term to it? Or can I still solve the ...
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95 views

Prediction for new data using trained Gaussian Mixture Model

I am not sure how to do the prediction for some new data using trained Gaussian Mixture Model (GMM). For example, I have got some labelled data drawn from 3 different classes (clusters). For each ...
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20 views

Kalman filter before or after outlier removal?

I am getting radar data points in form of (x,y) coordinate system relative to my position every ms.[around 10-15 data points]. Now, inorder to have better position estimate of the points, I would like ...
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15 views

How can I validate if a pattern is meaningful?

I am a financial analyst for a construction company. My goal is to develop an accurate sales model that is correctly reflects prior sales history (back testing) so I can then predict future sales. I ...
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2answers
216 views

Pattern recognition with time series analysis

I'm looking for some good pointers to pattern recognition with time series. Possibly something practical that can be easily understood. As a toy example, think about collecting data from an ...
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53 views

What is the next step after acquiring the parameters(means, covar, priors) from GMM via EM

I am comparing the results achieved from clustering via K-means and GMM. For comparison I have accumulated a dataset of images. The training set consists of 359 images. I used SIFT to extract the ...
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1answer
34 views

How well do Convolutional neural networks in other image domains?

I was recently trying out caffe and learning about CNN. So far I have seen that the model used by Krizhevsky performs really well in natural images. However I wanted to know how these models or CNN ...
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38 views

find group of rows in a matrix with pattern similar to another matrix

I've been scratching my head about this problem for some time: I have a big gene expression dataset (20k genes x 200 samples) in matrix A and i have a subset of this dataset (i.e. 40 genes x 200 ...
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51 views

Dirichlet process mixture model in Python

My question is concerned with the practical issues of using this model. I've tried to use Dirichlet process mixture model from Scikit learn python package to find a number of clusters in my data (1D ...
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314 views

Finding best neural network structure and inputs using optimization algorithm and cross-validation

I'm using optimization algorithm to find best structure+inputs of a patternnet neural network in MATLAB R2014a using ...
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29 views

Find linear subsets in a 2D point (xy) data [duplicate]

My problem is the very idea of how to start the analysis of 2D point patterns, specifically how to find linear trends within their spatial pattern. I have XY data points which are organized like in ...
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1answer
21 views

Supervised Pattern Recognition with Probabilistic Labels

I am interested in supervised pattern recognition problems where the the label associated with each pattern gives the probability of membership for each of the $c$ classes, rather than assigning each ...
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29 views

breakpoint analyses on multiple series: how to detect common points

I have 20 time series that span the same period (100 days each), from 4 species sampled at 5 different location. I made a loop to perform a breakpoint analysis on all of them, resulting in 0 to 3 ...
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1answer
69 views

detect line in geocoordinates

I have repeated samples of geocoordinates of activities in a city. In most of these samples positions will simply be random. In some samples, however, some percentage of the data will be arranged -- ...
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65 views

Order and similarity measurement

Let's say I have 10 different groups, and each group has its own string sequence. So, it should be like: ...
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3answers
310 views

Pattern mining on a small data set

I have a small data set 30 features/predictors and 30 observations. My target variable is Oil production and my predictors are well & reservoir properties (depth, trajectory, temperature, pressure ...
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37 views

Neural-Net style pattern recognition with an unknown/varying number of inputs?

Say for example I had a weighted graph such that each node had an associated value. The nodes' values are given by some function of the edge weights and the number of edges as well as the node's ...
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25 views

Walking recognition

I have walking samples from 20 different people. My aim is to detect which walking samples are from which person. I'm trying to achieve this by extracting "walking cycles" from each person's dataset ...
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1answer
108 views

detect line in scatter

I have repeated samples from the following process: Most samples will only contain points that are randomly distributed on a 2-dimensional plane. Sometimes, however, the sample will contain not only ...
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29 views

how to handle occlusion for face recognition?

If there some occlusion on face (such as sunglasses, mask, scarf), the recognition rate will decrease steeply? How to handle this case? I have do a survey, the PCA reconstruction method have been ...
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34 views

Anomaly detection of web browsing sequences

Please consider that I'm quite new to machine learning. I need to create models based on browsing patterns of web users and find deviations from that model. I'm using web server access log files. For ...
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1answer
28 views

missing value patterns

I am doing some data preparation with Python using Pandas and I am working with a dataset that has about 80 variables with missing values and I want to capture any patterns of missingness to cut down ...
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41 views

How many features to overfit the classification?

Recently, I have got some 'strange' comments from the reviewer of my paper. In my paper, I discussed a novel feature extraction method, and then I compared three classification methods for my binary ...
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3answers
73 views

Recognition of simple patterns and prediction

I have been doing supervised learning and classification with multilayer perceptron for some time. But now I need to use unsupervised learning to infer the presence of a pattern and I would need some ...
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29 views

Conceptual question on image pattern representation

I have a basic question regarding pattern learning, or pattern representation. Assume I have a complex pattern of this form, could you please provide me with some research directions or concepts that ...