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

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Training data set size and SVM classifier

I want to do a multi-class classification of human action recognition. I plan to collect data. So, How can I estimate the minimum data set size. What are the important parameters?
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13 views

Fraud detection use text mining [on hold]

I have 1 million unstructured text documents about the clients' information with metadata about the client name, viewers, location in the cloud. I want to fraud detection. How can I detected the ...
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10 views
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69 views

R: Finding relationships between 2 variables to determine any patterns in data

I am working on finding relationships/patterns between 2 variables (Type_A, Type_B). ...
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26 views

What are the benefits for semi-supervised learning over unsupervised clustering? Or any limitations?

I have another question about semi-supervised learning vs unsupervised clustering, what are the benefits and limitations? I have got some data with labels and some without labels. I performed ...
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17 views

Semi-supervised learning vs supervised learning, what are the benefits and limitations?

Just wondering if any previous work compared semi-supervised learning vs supervised learning? Currently, I have got both datasets with and without labeling. And therefore, it is intuitive for me to ...
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26 views

pattern recognition or clustering for analyzing seasonal data

I have a set of historical data for an event which is highly seasonal. The event can be held in spring and summer but it is not planned for fall and winter. I wanted to forecast days to the next event ...
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27 views

Valid result when adding two kernels with negative coefficient?

If $k_1$ and $k_2$ be a kernel in $ \mathbb{R}^n \times \mathbb{R}^n $. we know $k(x,z)=ak_1(x,z) + bk_2(x,z)$ (kernel addition) is still a valid kernel if $\: a,b \geq 0\,$ ($a,b$ is real numbers, ...
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144 views

two margin comparison and one conclusion?

I read following notes, and couldn't get it. any idea or hint would highly appreciated. a SVM classifier using a second order polynomial kernel. The first polynomial kernel maps each input data x to ...
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1answer
23 views

variance in test accuracy will increase as we increase the number of test examplesěč

I see this statement on 1 that say a True statement on Machine Learning Context. The variance in test accuracy will increase as we increase the number of test examples. my challenge is why ...
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15 views

How to visualise the uncertainty of the classification?

I used SVM to do some classification, and SVM can output some probabilities (likelihood) value measuring how likely each data to be one particular class. For example, Data point 1: 90% (class 1) 5% ...
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2answers
44 views

Semi-supervised Learning Training

I have got some data partially labelled. Therefore, I would like to apply semi-supervised learning for this dataset. Basically, I trained the Support Vector Machine (SVM) using the data with labels ...
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14 views

Importance of the norm of the weight vector in the perceptron algorithm

I have exhausted all possible searches online on the role of the norm of the weight vector in binary classification. The only information i am getting is that it prevents over-fitting. I don't see how ...
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22 views

Find repetitive patterns in matrices below

How can I identify the repetitive patterns from the matrices below? My problem is that the patterns in the matrix are different from matrix to matrix (dependent on the input data). I need some machine ...
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16 views

How to Calcuate Segment & Symbol Periodicity

I want to calculate segment and symbol periodicity using R. Has any one done it before as i am relatively new to R? i have a lot of timeseries with irregular sporadic data and i want to find out if ...
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7 views

formula for extrapolating recognition rate as a function of number of possible matches

What would be a formula for extrapolating behavior of an algorithm that was tested with small number of false positives, say 10 or 100 but I want to know the rate with 1000. E.g., the recognition rate ...
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21 views

Determining if data follows a Sigmoid function given data that does

I am essentially trying to determine if some gene expression data I have follows as circadian pattern. Currently I have gene expression data for genes know to follow a circadian pattern. I want to ...
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1answer
38 views

k-means and other non-parametric methods for clustering 1 dimensional data

I know that a few people asked this question before and that clustering is not the best method for 1 dimensional data. However, I saw that in some published papers people used k-means clustering for 1 ...
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25 views

Generalised itemset mining?

As far as I understand, the common approaches to itemset mining assume the following: An itemset is a conjunctive logical clause (which in some approaches allow negation) All items are in principle ...
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40 views

analysis of bank account record

I am new to the field of time series analysis, but I would like to have a look at my bank account and determine my spending habits. I read a lot about clustering of multiple time series but I think I ...
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1answer
41 views

Sequential pattern matching in time series data

If I have a time series set such as x=[0,2,5,2,3,1,0] that represents an artifact. What is the best way to match a similar set as x in a larger data set y?
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120 views

Can a Naive Bayes Model predict using pattern alone?

Say I have a set of data abc-def-ghi jkl-mno-pqr stu-vwx-yza and lots of other training samples which are catagorized as **names*. The above dataset does not have ...
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1answer
78 views

Mortgage loan predictive analysis

I have hundreds of thousands of mortgage loan historic records that look like these 2 examples: ...
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2answers
120 views

Finding occurrences of specific patterns in time series

I have to locate occurrences of Cyllinder, Bell and Funnel patterns in univariate time series $X$ of gamma-ray sensoring. This is a specific case of the general CBF synthetic problem found in a few ...
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90 views

Pre-processing before digit recognition for NN & CNN trained with MNIST dataset

I'm trying to classify handwriting digits, written by myself and a few friends, by usign NN and CNN. In order to train the NN, MNIST dataset is used. The problem is the NN trained with MNIST dataset ...
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7 views

Separability measures

I am just studying pattern recognition. In that regard, my question is Why we need separability measures? Would you please give me detail explanation and suggest some books to read?
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9 views

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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8 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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23 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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15 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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16 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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39 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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14 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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45 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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19 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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21 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
64 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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46 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
74 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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37 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
96 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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2answers
613 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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10 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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21 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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1answer
40 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
455 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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1answer
103 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 ...