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

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11 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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25 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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23 views

Finding rules in a dataframe in R [closed]

If I have a file like this start end [1,] 1 1 [2,] 2 2 [3,] 4 4 [4,] 5 5 [5,] 7 7 [6,] 8 8 Is it possible to make rules ...
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16 views

Finding duplicate values in a single string of characters in r [closed]

So, I have a string like this. "1101101101" Now, here as we can see, the number '1' is appearing at positions ...
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3answers
51 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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23 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 ...
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49 views

good practice for dimensionality reduction using Principal Component Analysis (PCA) and/or Linear Discriminant Analysis (LDA)

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) best practice Assuming I have a dataset for a supervised statistical classification task, e.g., via a Bayes' classifier. This ...
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28 views

What is the simplest way to classify airplan manuvers?

Suppose we have declared four motion types for air-plane. If we represent each maneuver with a trajectory line, what is the best classification method to retrieve the trajectory pattern with a similar ...
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15 views

visualize the naive bayes with k-fold cv

I have done the classification using naive Bayes as a classifier, and applied 10-fold CV.I know that I can get the mean and variance of the result. However, how can I plot the classifier performance? ...
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18 views

Benchmarking model in speech recognition with different language

My supervisor asked me to benchmark my method in classifying speech signal with other language. I am doing Malay language speech recognition. To benchmark my method/feature used, I need to test ...
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25 views

Multiple Discriminant Analysis, Linear Discriminant Analysis, and Multidimensional scaling - how are they related?

Some time ago when I took a Pattern Classification class, the "concept" was introduced as Multiple Discriminant Analysis: You want to project your data onto a subspace (if you are interested in ...
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40 views

Testing a 2D point cloud for banana shape

I have many point clouds of a small size (say <200 points) in 2D. Some of them are isotropic and can be modelled as a single point. Others are elongated and curved so that they can reasonably be ...
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18 views

How Sensitive Are Neural Networks?

CrossPost: https://stackoverflow.com/questions/24301472/how-sensitive-are-ff-neural-networks I am aware of pruning, and am not sure if it removes the actual neuron or makes its weight zero, but I am ...
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21 views

Recognize spatio-temporal patterns correlating with events

I am trying to recognize a spatio-temporal pattern in my spatio-temporal input sequence X. The occurrence of the pattern is roughly temporally correlated with another event E1. For example I have ...
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12 views

Time series pattern identification - SVD/SSA?

I've looked over other posts regarding time series data, and am unsure if the mentioned methods would apply to what I'm trying to do, since I'm not familiar with pattern analysis methods: I have time ...
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1answer
39 views

Having a Neural Network recreate what it's learned

I've created a basic Neural Network that learns from basic information and can verify whether or not a piece of information matches it's parameters from a match percentage. Conceptually however, I ...
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75 views

Finding all largest sequences

What would be a good / efficient algorithm or approach to find all the largest sequences within a list of chains with varying lengths? For instance these chains: ...
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20 views

How can you use HMMs and ANNs for on-line handwriting recognition?

I've asked this question on cs.stackexchange before. It has a 20-hours remaining bounty there. On-line handwriting recognition is the task of converting a series of $(x(t),y(t))$ coordinates to ...
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27 views

HIdden Markov model training Baum Welch, concavity log likelihood

Hi i'm developing an hidden markov model algorithm training with multiple sequences. The recognition rate is good but i have doubts about the shape of the curve of log likelihood obtained from the ...
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31 views

Subtracting mahalanobis distance in one direction from total

Sincere appologies for what may be a stupid question, I'm new to pattern recognition and have exhausted all the textbooks which are aproachable to a beginner. I have substantially reworded this post ...
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2answers
62 views

Does fastICA require PCA to run at first?

I reviewed an application based paper saying that applying PCA before applying ICA (using fastICA package). My question is that does ICA (fastICA) requires PCA to run at first? This paper mentioned ...
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29 views

Image vectorization in matlab

I need to convert images into vectors (image vectorization). I have 165 images in total, divided into 15 subjects of 11 images each. Following is code i have written to convert images into vectors. ...
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2answers
136 views

Confused about sensitivity, specificity and area under ROC curve (AUC)

Just read a unpublished paper for review purpose. The reported results like Leave-one-out cross validation sensitivity is 95%. Leave-one-out cross validation specificity is 100%. Leave-one-out cross ...
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1answer
42 views

Face Recognition approach DCT features

Face Recognition approach based on entropy estimate of the nonlinear DCT features proposes to use maximum entropy estimate of the DCT of the pixels. My question is maximizing entropy would mean ...
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29 views

Time series image data classification / video image classification

I am working on classifying video frames into two classes, positive and negative. e.g. if a particular pattern appears in a frame that frame will be classified into positive, otherwise negative. But ...
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27 views

Smart application of transformations in digit recognition

So I'm working on some machine learning code to recognize the digits 0-9 using singular value decomposition, followed by a least squares comparison with the first 15 or so singular vectors as my ...
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29 views

Methods for temporal patterns extraction

For example a video or series of images, or usage patterns data on a website, or a univariate time series, is there some flexible methods for extracting patterns of any length, such as head ...
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80 views

Comparison of close data sets

I'm studying around 100 sets of temperature ($N_{sample}=500$), which depends $4$ explicative variables such as power or speed. The dependency is always the same in each set, but sometimes the mean ...
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37 views

Which type neural networks for time series classification

I would like to use neural networks to classification of time series ( I have some Patterns and I want to adjust input time series to an appropriate class) -ist it possible to do this job with ...
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58 views

What's wrong with my Kernel algorithm (Kernel SVD)?

I have a user-item matrix $A$ as data input, which is a sparse matrix containing a large number of missing values (as zeros). Each row is a user, and each column is an item. Generally, I am conducting ...
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113 views

What are the advantages of kernel PCA over PCA?

I want to implement an algorithm in a paper which uses Kernel SVD to decompose a data matrix. So I have been reading materials about Kernel methods and kernel PCA etc. But it still is very obscure to ...
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79 views

Is it OK to increase validation checks and decrease min gradient while training neural network?

My input vector is a 130*85 matrix and my target vector is 130*26 matrix. I am using the below parameters for training the network with 60 hidden nodes. ...
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34 views

Use PCA for pattern recognition

I have always used PCA as a preprocessing techniques. There are some people that use it for pattern recognition. Once I used pca to project my data in a 2 dimensional space and then I observed that ...
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38 views

How to calculate false accept and reject rates in pattern recognition?

I am working on a vein pattern recognition project based on SURF algorithm and Euclidean distance. I have completed my program to find the maximum and minimum distance between vein features and find a ...
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34 views

Given 3 discriminant functions I was able to classify 2D patterns, but how do I plot decision boundaries via matplotlib?

I have implemented the discriminant function and was able to classify the 2D patterns (via Python), but I have troubles thinking about an approach to plot the decision boundaries. Hope anyone has an ...
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1answer
108 views

How to define the maximum k of the kNN classifier?

I am trying to use kNN classifier to perform some supervised learning. In order to find the best number of 'k' of kNN, I used cross validation. For example, the following codes load some Matlab ...
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1answer
55 views

Cascade Combination of Kernel Functions

I have a question regarding machine learning and specifically kernel functions. Suppose we have a Kernel function, say $K(x)$, and also another distinct one, say $K'(x)$. I want to know is $K(K'(x))$ ...
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21 views

Measuring the standard deviation in Pattern recognition

Sometimes in pattern recognition say Character recognition, Hamming distance is used although there are other distance measures. But if the pattern is represented in (1,0,-1) then Hamming distance is ...
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47 views

Linear Discriminant Analysis matrix dimension

I am trying to implement Linear Discriminant Analysis for face recognition. I have 3 classes and each classes have 10 image each. The dimension of matrix in class A, B and C is 10*500 .So each row ...
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39 views

Within scatter matrix linear discriminant analysis

I am trying to implement Linear Discriminant Analysis. I have 10 classes and each class has 3 observations at various instances: ...
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55 views

anomaly detection on logs data

I wonder , if someone know the open source anomaly detection algorithm on computer log ? For an example , computer log look like as mentioned below : "value UL-CCCH-Message ::= { integrityCheckInfo { ...
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95 views

Normalized cross correlation vs Euclidean distance in template matching

What is the difference between normalized cross-correlation and Euclidean distance in pattern recognition? -- especially if we want to do recognition with template matching. I understand about ...
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1answer
87 views

How to interpret the number of k in k-nearest-neighbour classifier?

I have done some classification work using a k-nearest-neighbour classifier (kNN). And the classification performance is evaluated using cross-validation method. Some testing code from Matlab Help are ...
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2answers
222 views

The difference of kernels in SVM?

Can someone please tell me the difference between the kernels in SVM: Linear Polynomial Gaussian (RBF) Sigmoid Because as we know that kernel is used to mapped our input space into high ...
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1answer
61 views

Feature selection for pattern mining

I must find frequent patterns in temporal data, using a method that was imposed to me. This tool has problems handling these data: processing is long and takes a lot of memory. So, I would like to ...
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0answers
15 views

Reference Request: Human speech extraction using Machine Learning

I am trying to extract human voice from a noisy clip and studied some test upon it like, voice clipping using deep learning or MLP ann etc., then speech identification using a sequence based ...
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98 views

Pattern Recognition in Practical Problem in R

I am using R for last 4 months with basic test analysis, regression models, ANOVA etc. Now I am looking into a particular problem. In words problem can be stated like, A particular machine got a ...
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2answers
331 views

Can machine learning find all sort of crazy connections?

If you try a real thoroughly won't a computer find all sort of silly patterns? Messages from ETs in the bible rainy Sundays in China or Australia -> the chances of your sport team win reading many ...
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29 views

Bayesian parameter estimation homework problem

For BPE approach,for p($\theta$)~U(0,1) show that p(x|D)= $1/n+2[(x+ \sum_{k=1}^n(x_k)!)$ $ (n+1-x-$($\sum_{k=1}^n(x_k)$!]$/$[$(\sum_{k=1}^n(x_k))$! $(n-\sum_{k=1}^n(x_k))$!] I have tried using the ...
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1answer
44 views

Question about computing Bayes Error - with or without loss function?

I am new to Bayesian Decision Theory and don't understand the following concept: So from what I understood, the Bayes error is used to report the performance of a Bayes classifier in terms of the ...