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

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Prerequisite reading before Andrew Ng's machine learning course

I have basic understanding of probability, statistics and matrices. By basic, I mean I can understand the khan academy lectures on these topics. With this understanding , I proceeded to listen to ...
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7 views

Learning from sparse label products

Consider the following binary classification problem $f(\mathbf{X})\rightarrow\mathbf{Y}$ where: $\mathbf{X}$ = Feature matrix $\mathbf{Y}$ = Product of several label (binary) vectors, i.e. ...
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Generating text data for training for doing named entity recognition and extraction

I'm trying to build an algorithm for doing named entity extraction. It goes like this. There is a large set of text documents [communications], from which specific information has to be extracted. The ...
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1answer
22 views

Predicting the direction of moving a object in R

I am trying to produce a model that classify the direction of a moving object. In the figure we see a single projection of 3D space where an object was moved up and down (red) vs up and down together ...
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1answer
14 views

ordinal classification using C5.0

My question is about machine learning to predict ordinal variables. Most ML models for classification that I have seen do not make any assumption about the order of different categories. I can see ...
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15 views

Machine learning algorithms for panel data

In this question - Is there a method for constructing decision trees that takes account of structured/hierarchical/multilevel predictors? - they mention a panel data method for trees. Are there ...
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1answer
38 views

SVM RBF performance on “dissimilar” data

I've been studying the performance of machine learning algorithms on "dissimilar" data (that is, prediction on new data that are not that "similar" to the training set) and I came up with this ...
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1answer
28 views

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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23 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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34 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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23 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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1answer
19 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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1answer
35 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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6 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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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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6 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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8 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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1answer
129 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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10 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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8 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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1answer
48 views

Types of artificial intelligence with good results [closed]

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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19 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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1answer
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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1answer
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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1answer
50 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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808 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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1answer
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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7 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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10 views

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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14 views

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
146 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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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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1answer
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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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, ...