Methods and principles of building "computer systems that automatically improve with experience."

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54 views

What are the general strategies in creating a Probabilistic Graphical Model?

While there is lot of theory and probability in the background to understand, I wanted to know if there are any resources/quick pointers on what to consider while modeling a problem using Bayesian ...
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1answer
18 views

Use of infinity norm instead of SSE for machine learning accuracy?

Are there any examples or arguments in favor of using an infinity norm (or equivalent) over sum of squared errors or root mean squared error for evaluating machine learning algorithms?
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1answer
13 views

Ontology and semantic web [on hold]

anyone know from where (Link / website etc.) Can be used to get already build ONTOLOGY (mean in ready to use form ontology) as I am looking for the book ontologies? Thank you
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0answers
23 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 ...
5
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1answer
3k views

The input parameters for using latent Dirichlet allocation

When using topic modeling (Latent Dirichlet Allocation), the number of topics is an input parameter that the user need to specify. Looks to me that we should also provide a collection of candidate ...
2
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1answer
116 views

Machine-learning input data distribution

I'm trying to build a binary 1/0 ML classification algorithm, and was thinking about how to set up the input dataset. If the event I want to predict (the 1's) occur relatively less frequently in the ...
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2answers
157 views

A multi-label classification for tagging short text

I am fairly new in the area of text mining and want to practice my skills a little. I have the following task at hand which I want to work on. I have a large list of short texts (~100.000) and every ...
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1answer
54 views

Trying to understand NMF

I'm trying to understand how NMF derived, and I got the basic idea of NMF, that is, it tries to appoximate original matrix $V$ with $WH$, where $V$ are non-negative, and $W,H$ are constrained to be ...
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8 views

What is the relationship between separable SVM test error bounds and soft-margin SVM test error bounds?

Can I compute the bounds for a soft margin SVM by taking the VC dimension for an SVM and using the misclassified examples as train error? Does the inequality from wikipedia's VC dimension page hold ...
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142 views

Quantitative results of clustering analysis

Currently, I am doing a clustering analysis for two sets of data. One smaller dataset (about 100 data) got ground truth labels, and one larger dataset (about 2000 data) has no ground truth labels. ...
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1answer
77 views

Linearly dependent features

I have a matrix A of 1000 observations (rows) and 100 features (cols). I would like to find: Linearly dependent features so that I can remove them and simplify the problem. rank(A) gives me 88, ...
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3answers
120 views

Optimal classification model for translating words

I have the following problem: I have a set of English words which I want to translate to Dutch. Of each words I mined a set of possible translations. For example, for the word "Eighteen" I obtained ...
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2answers
20 views

What's the best algorithm type for low-dimensional grouping

I'm looking for some advice on directions to head in a project I'm working on. Basically what I want to do is identify general (of varying size) groups in a 2-D grid of points belonging to one of ...
0
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1answer
109 views

How to find important features in this problem

I was just thinking how ML techniques can be applied in the retail industry. Suppose we have data from a retailer who deals with apparel and cloth in this format and for each item there are ...
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0answers
39 views

Supervised classification of a network

Here is the form of my data, basically it is a network, with each node has one target attribute, one feature value (a value correlated with the target attribute bale), and the edges between the nodes ...
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1answer
56 views

Strategy for Analyzing Data

I have been learning about Machine Learning (via Udacity) and Statistics (via Coursera) the past few months and trying to figure out a good way to combine them for a general approach to explaining ...
3
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1answer
158 views

Difference of Prediction between Graph Representation and Data Matrix Representation

In data mining, data can be usually represented in different forms such as records of a matrix, graphs or ordered data. While we find in research different papers addressing methods or solutions for ...
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2answers
158 views

ML vs MAP estimation, when to use which?

ML = Maximum Liklihood MAP = Maximum a-posteriori ML is intuitive/naive in that it starts only with the probability of observation given the parameter (i.e. the likelihood function) and tries to ...
3
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1answer
155 views

Measuring and analyzing sample complexity

I recently stumbled upon the concept of sample complexity, and was wondering if there are any texts, papers or tutorials that provide: An introduction to the concept (rigorous or informal) An ...
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2answers
489 views

Why would anyone use KNN for regression?

From what I understand, we can only build a regression function that lies within the interval of the training data. For example (only one of the panels is necessary): How would I predict into the ...
2
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1answer
72 views

Confusion: different definitions of MAP estimation in Graphical Models (MRFs)

The "classical" MAP estimation: $$\hat\theta = \arg\max_{\theta}P(\theta|\mathbf{x})$$ where $\mathbf{x}$ are the observations and $\theta$ are the parameters. In this book chapter (page 6, second ...
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21 views

How to calculate multicollinearity of binary variable with other predictors in regression model?

VIF can be used to calculate multicollinearity of continuous variable in regression models. But VIF will only work for continuous variables because this is calculated by running a linear regression ...
0
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2answers
178 views

Test data generation for neural network handwriting recognition

Can someone share some Octave/Matlab code or algorithm to pre-process a photo taken from mobile camera of a handwritten digit. After pre-processing, the data should have similar characteristics to ...
2
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1answer
175 views

Comparison of two classifiers based on precision/recall/F1 only?

For two classifiers h1 and h2 I have the precision, recall and F1 score as a percentage (along with the original labeled data set that they were tested on). If I had access to which samples each ...
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1answer
102 views

Extract important features

Here is my situation: - A huge amount of data - 600 features - Only one class is provided Now, my question is how can I reduce the number of features to important ones? In another word, all of these ...
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37 views

Dichotomizing Continuous Variables in Regression: Good or Bad?

I believe Dichotomizing(also called bucketing/binning) of continuous variable is not always a good idea. My colleague while building regression model always bins continuous variables and only keep ...
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17 views

Intuition on One Class Support Vector Machines

I am having trouble understanding how one-class SVMs work. They were introduced in a paper by Scholkopf and others (and can be found here). One-class SVMs perform "novelty detection", where a point ...
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36 views

What is a convolutional neural network

I have been studying neural networks and I recently found out about deep learning and convolutional neural networks. Can someone give me a newbie introduction to convolutional neural networks, what ...
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1answer
17 views

Affinity propagation comments

I was looking into affinity propagation for my similarity matrix problem and thought it would fit well. However, browsing literature I found this comment that basically breaks both legs of affinity ...
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4answers
8k views

What does the hidden layer in a neural network compute?

I'm sure many people will respond with links to 'let me google that for you', so I want to say that I've tried to figure this out so please forgive my lack of understanding here, but I cannot figure ...
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1answer
55 views

Data preparation and machine algo for ad click prediction

I am an ml noob. I have a task at hand of predicting click probability given user information like city, state, os version, os family, device, browser family browser version, city, etc. I have been ...
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2answers
32 views

Classes distribution in training set

In my actual data class A has 90%, class B has 9% and class C has 1% (numbers are made up for sake of simplicity). Now I want to prepare a training set for my classifier (I plan to use Vowpal Wabbit). ...
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1answer
1k views

Interpretation of a WEKA result buffer - confusion matrix and performance

I want to know how to get several performance measurements of a generated WEKA model. Note that I am predicting a two-class variable, Alive or ...
0
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1answer
87 views

How to set the radius value in self organizing map?

I'm training the self organizig map, I need to set the value for the radius of it. is there any method to find the optimum radius size ?
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1answer
96 views

Suggestions needed about classifier fusion

I'm working on a classification problem which involves two classifier to observe a single event. I'm providing a high level description of the problem without going into the technical details (the ...
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0answers
8 views

Use cases for P-Kernel for SVMs

I've been reading the book by Cristianini on Kernels (2004) where generative kernels (like p-kernel and fisher-kernel, not to be confused with polynomial kernel!) are described. I am interested in ...
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2answers
50 views

Understanding differences between large and small dimensional data when implementing algorithms

I'm working on a local outlier factor implementation based on the wikipedia entry : http://en.wikipedia.org/wiki/Local_outlier_factor This article seems to explain it in just two dimensional data. ...
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1answer
100 views

Discriminative vs. Generative Models

This has be asked before, but I still have not grasped it completely. I know that generative models model the feature distribution and that this includes modelling the P(x|y) and P(y), which are not ...
0
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1answer
19 views

Question of unary term (data term) of the graph cut method

I am trying to apply graph cut method for my segmentation task. I found some example codes at Graph_Cut_Demo. Part of the codes are showing below ...
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19 views

Comparison of supervised learning algorithms with different data types

I've been looking for review type papers of supervised learning techniques that focus on the type of data being used to train e.g. factors with many levels, binary factors, continuous variables etc. I ...
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2answers
84 views

Class labels in data partitions

Suppose that one partitions the data to training/validation/test sets for further application of some classification algorithm, and it happens that training set doesn't contain all class labels that ...
1
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1answer
46 views

Data Conversion to Standard data format in hierarchical Dirichlet process

I'm trying to test the performance of posterior inference on a set of documents with hierarchical Dirichlet process for topic modeling. How can i convert my data (document) to standard data format ...
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22 views

How to prepare my data for SVM classifier in matlab

I am new to SVM and Matlab. I would like to have an example how to prepare my data to be as input to the SVM classifer (using libsvm) let us assume that i have a group of words first i have ...
0
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1answer
27 views

In a neural network of n features which predict a continuous variable X, how to tell the feature which contributes the most to the output value X?

Say I have a neural network which uses some input features say N, some inut layers say L which predict a continous variable say X. Can we say which features or combination of 2 features of the initial ...
2
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1answer
290 views

Forecasting optimization techniques in fantasy baseball

I am currently trying to build a better forecasting model for my fantasy baseball roster. I currently am using commonly accepted projected season statistics (ZiPS from Fangraphs) to determine the ...
4
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3answers
366 views

How to handle high dimensional feature vector in probability graph model?

I was doing some NLP related stuff which involves training a hidden Markov model, and use the model to segment sentences. For every sentence, I translate the tokens into feature vectors. The features ...
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0answers
32 views

predicting time series with support vector machine using R

I am planning to do time series prediction using support vector Machine. I could not find any materials about time series application of support vector machines using R or Mat-lab. Similar question ...
8
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2answers
367 views

Where and why does deep learning shine?

With all the media talk and hype about deep learning these days, I read some elementary stuff about it. I just found that it is just another machine learning method to learn patterns from data. But my ...
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1answer
248 views

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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21 views

Live selection of movie to suggest based on similarity of users

I am working with movie selection for users. 1 ) One of the first ways I thought was taking all the clicked only movie data and building decision trees out of it. Then when input is passed, the ...