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

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Mean field variational inference

In Chris Bishop PRML book p.465 equation 10.6, the derivation doesn't explain why exactly the term $\int q_j ln(q_j) dz_j $ was generated, is not that term supposed to be multiplied by constant, did ...
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17 views

Maximum Entropy classifier, high precision but low recall

I'm working on a sentiment analysis study of twitter data using the Maximum Entropy classifier. I've gathered dozens of thousands of tweets. To produce features, I used unigram, bigram and dictionary. ...
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30 views

What is maxout in neural network?

Anyone can explain what does maxout layer do in neural network? How to perform it? What does it different to normal activation function? I try to read the 2013 "Maxout Network" paper by Goodfellow et ...
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21 views

What is the derivative of a matrix with respect to f? The matrix has softmax function in it

I need the derivative of W, which has the following expression. W is matrix which contains entries from softmax function. I couldn't find the derivative.
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15 views

Grid search error in LIBSVM while optimizing C and g parameters

I am using libsvm for a one-class classification problem. I am trying to select the ideal C and gamma parameters for different kernels(polynomial, linear and rbf) I am using the suggested matlab code ...
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30 views

How to standardize text data for training Neural Networks?

I want to train neural network with text data(natural language) as input for classification purpose. One way for standardizing text data for neural network is to use N-GRAM/SKIP-GRAM representation ...
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6 views

How to shorten the detection time of adaboost algorithm?

I'm working on a license plate detection using OpenCV's adaboost algorithm. However, after training, it shows that the detection takes 3200ms for a single image, where the image size I used is ...
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5 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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16 views

Identifying topic name

When we perform Latent Dirichlet allocation on a set of documents to cluster, just assume give n=5 topics. How can we assign the topic name for these topics after performing LDA? I would like to give ...
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9 views

Diference between glm and bigglm estimates

How does bigglm function in biglm package work for logistic regression? I thought that it is not possible to calculate LR on chunks of data and then merge results. Will glm and bigglm yield ...
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29 views

ANNs and mixed data-type problems

I did some research but I'm not quite sure if ANNs, more precisely MLPs, are able to handle mixed data-types (e.g ordinal and metric scaled variables) like in the German Credit data set without ...
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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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7 views

XOR backpropagation convergence

I've implemented 3 supervised training algorithms: rprop, online- and batch backprop with momentum. I have the simple XOR test, and I measured how many times they converge out of N iterations. My ...
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112 views

Deep learning algorithm

What's the difference between deep belief network and deep convex network?
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24 views

Machine Learning approach to solve this selection problem?

I have a set of items S. items can be joined to groups consisting of up to x items. For a group of items i can derive a score Y using some unknown performance measure. What would be the most efficient ...
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8 views

How can recurrent neural networks be used for sequence classification?

RNN can be used for prediction, or sequence to sequence mapping. But how can RNN be used for classification? I mean, we give a whole sequence one label.
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7 views

How to Mine Tree Structures?

To learn similarities/differences between different instances (that are in the form of tree), what are the suitable methods/approaches? I know kernel methods and particularly tree kernels, but would ...
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48 views

Types of artificial intelligence with good results [on hold]

I have been looking into artificial intelligence for some time now. I am wondering what branches are still in active research and have some good/interesting results. The two that I have looked in so ...
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5 views

ImageNet: what does top-five error means?

One of the evaluation method for ImageNet Competition (classify 1,000 categories images) is top-5 error, what does that mean? See: http://www.image-net.org/challenges/LSVRC/
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26 views

Plot that shows which attribute has the most effect on class?

I'm playing around with two datasets: Mushrooms and Breast Cancer. I'm trying to form a hypothesis of which attribute would have the most effect on the class when making predictions about the class. ...
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5 views

Nonnegative Matrix Factorization coefficient matrix normalization in microarray data

I am confused by the coefficient matrix in nonnegative Matrix Factorization. Suppose I have a time course microarray data matrix as V (m*n), which is decoded by ...
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17 views

Confidence Interval of Calculating Precision

The problem I'm trying to solve has the following setting: Let $X_1, \dots, X_N$ be a data set where each $X_i \sim Categorical(p_{TP}, p_{FP}, p_{TN}, p_{FN})$ s.t. $\sum\limits_{k \in ...
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1answer
15 views

Distance from hyperplane in SVM rbf kernel in R

I am running ksvm in R(using kernlab package) for a highly imbalanced data.Is there any way i can get the distance of my test data points(each of dimension 8-10) from the hyperplane?so that i can ...
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21 views

How to fit a single quadratic term to a regression

I have a high dimensional multivariate model and am fitting linear weights to each of the $N$ free variables using a classic stable SVD matrix solver. This works. I want to improve the fit by using a ...
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10 views

What techniques are used to prevent overfitting in DSN

A Deep Stacked Network (DSN), is a ensemble learner, which roughly works by training a single hidden layer neural network on the inputs and target outputs, then training another which takes an input ...
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24 views

A single document as input to LDA?

We use topic modelling usually on a collection of documents - which makes the input. But what if I only have a single document where I want to see the underlying topics in it? I have heard that you ...
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14 views

Non parametric estimators for noisy functions

Suppose there is a function $f(a,b,c,\ldots)$ of $M$ variables (fixed numbers, not random variables). Add some Gaussian noise to this function: $$ g(a,b,c,\ldots) = f(a,b,c,\ldots) + ...
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29 views

How to use geometric proximity in classification

I am doing a classification of certain regions of an image. Let's say I have done the classification, and some classes have been classified positively (negatively) with high probability. For my ...
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49 views

Gradient of Log-Likelihood

Considering the following functions I'm having a tough time finding the appropriate gradient function for the log-likelihood as defined below: $a_k(x)=\sum_{i=1}^D w_{ki}\cdot x_i$ $P(y_k|x) = ...
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8 views

Classification problem with constraints

I am trying to solve a classification problem with constraints and need advice on how I should approach it. Here's the problem: Given N observations, FLAG_j, j=1,..,N (this is a binar variable), and ...
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786 views

What exactly is a Bayesian model?

Can I call a model wherein Bayes' Theorem is used a "Bayesian model"? I am afraid such a definition might be too broad. So what exactly is a Bayesian model?
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23 views

Reparameterization of probability distribution (spike and slab)

I try to understand a statement in this paper: http://papers.nips.cc/paper/4305-spike-and-slab-variational-inference-for-multi-task-and-multiple-kernel-learning.pdf In particular, I am talking about ...
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17 views

Feature engineering with non-fixed length vectors?

I have a bunch of data that looks like this: ...
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6 views

max margin vs max posterior/likelihood advatages

I am working on some parameter learning approaches for image classification. What is the differences between the following two for image classification? max margin methods maximum likelihood/ ...
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2answers
39 views

Mixing proportion $\pi$ in Mixtures of Gaussians

I am trying to understand a little better mixtures of Gaussians and their generative approach in general. For a mixture of Gaussians we start with this formula: $$p(x)=\sum_{k=1}^{K}\pi_{k}\cdot ...
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Profiling high-scoring clusters in a multi-dimensional feature space

I have a large amount of samples, which have a multi-imensional feature vector associated with them. Each sample has a "score", and the length of the feature vector is substantial (n>100, and in ...
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number of feature maps in convolutional neural networks

When learning convolutional neural network, I have questions regarding the following figure. 1) C1 in the layer 1 has 6 feature maps, does that mean there are six convolutional kernals? Each ...
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2answers
145 views

Times series analysis vs. machine learning?

Just a general question. If you have time series data, when is it better to use time series techniques (aka, ARCH, GARCH, etc) over machine/statistical learning techniques (KNN, regression)? If there ...
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36 views

Which ML algorithm is suitable for the following problem?

Assume i have x states each defined by an n-dimensional feature vector. In addition i have a set of actions which can be taken in each state resulting in a state action score. What would be an ...
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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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2answers
82 views

Detecting Bimodal Distribution

I have histograms of audio signals where they have bimodal "normal" distribution. What I want to do is to detect these subpopulations inorder to have a threshold, this is meant to divide the values ...
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14 views

What can I possibly get from my data to find what I need?

I am an end-user of a program. This program returns an output based on an input (a file + a database). I have made a few tests with differents files and databases, then constructed a CSV file of the ...
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294 views

Request: Clever Things to do with Naive Bayes

I am trying to drive up the performance of a Naive Bayes classifier, and I haven't been having terribly much luck. I've been working in Weka, but have enough knowledge of R to (possibly) implement ...
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23 views

Unbiased Estimator of Product

Suppose there are stationary times series $\{A_i\}_{i=1}^{T},\{B_i\}_{i=1}^{T},\{C_i\}_{i=1}^{T},\{D_i\}_{i=1}^{T}$, which may not necessarily be independent processes. We know that ...
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1answer
42 views

Starting to apply theoretical “data science” learnings to real-world data sets

I've been reading a number of data science books recently (Python, R, etc), plus attempting a number of the MOOC courses, and so on, and the content is reasonably consistent: regression, ...
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29 views

the Chi-squared distribution and Mahalanobis

I'm doing some simulations in C++ and OpenGL (2D and 3D) for navigating a robot in unknown environment known as SLAM. I'm using Extended Kalman filter as an optimal estimator. In SLAM problem, once ...
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1answer
38 views

Eigenfaces in R: How to reconstruct original features from principal components? [duplicate]

I've performed PCA on face images dataset and I'm not sure how can I use the most informative principal components to show the "reduced" image. The original image is 96*96 pixels (96*96 = 9216) and I ...
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26 views

Binary classifier via Mahalonobis distance

In a recent conversation with a colleague at univerity, they mentioned that for a certain problem, we can "just use a binary classifier". When I inquired as to how they would train, they said "No ...
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1answer
17 views

Check a status of training process in R

I'm training a model using caret package in R for almost 3 days. The calculations are running in parallel (multiple processes). Unfortunately there is no output in ...
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69 views

Modelling Technique

I have a 5 years of Cargo insurance (goods transportation insurance) data. I need to predict the claim amount based on their policy date and some other variables like mode of transportation, Country ...