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

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Approximating median of the sum of independent, non identically distributed RV for small n

I have observations for positive, non-identically distributed RV $x_i$, it can be assumed that RV are independent. I am interested in $y = \sum_{i=1}^n x_i$. For example, $x_i$ can be the time for ...
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1answer
61 views

Trouble training Neural Network

I'm trying to use Encog to define an artificial neural network in order to process this dataset (6 inputs, 2 yes/no outputs), but I can't get any lower than ~65% error. The NN is feedforward with ...
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9 views

when does kernel based method better than the regular

I am used with linear models. I can see rising use of kernel based method particularly in machine learning. The following is example Gaussian kernel using gausspr ...
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19 views

kernels and similarity (in R)

I am trying fit different kernels to calculate similarity matrix in R. Here is example data - X matrix : ...
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166 views

Why discriminative models are preferred to generative models for sequence labeling tasks?

I understand that discriminative models, such as CRF(Conditional Random Fields), model conditional probabilities $P(y|x)$, while generative models, such as HMM(Hidden Markov Model), model joint ...
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10 views

Neural-Net style pattern recognition with an unknown/varying number of inputs?

Say for example I had a weighted graph such that each node had an associated value. The nodes' values are given by some function of the edge weights and the number of edges as well as the node's ...
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2answers
335 views

Differences Between Logistic Regression in Statistics and in Machine Learning

I just found out that machine learning also has logistic regression as one of its methods. Can someone please tell me the differences between logistic regression in statistics and machine learning? ...
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1answer
67 views

In EM derivation why can I sum over the iid variables in the conditional expectation?

In EM when you take the expectation: $E[\log P(y,x \mid \theta)\mid x, \theta']$ $= \sum\limits_yP(y\mid x, \theta') \log P(y,x\mid \theta)$ I understand this but the following part I don't ...
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16 views

Low pass filter to maintain edge information

I am looking for a kernel as low pass filter that satisfy as:I must find a kernel that statisfies as follows: In the my reference paper, the author suggest gaussian kernel that is The gaussian ...
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78 views

Question regarding parameters and variable selection in Mahout algorithm for logistic regression

Below is the list of parameters in Mahout logistic regression. What does "passes" mean? In detail please --passes passes the number of times to pass over the input data ...
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17 views

How to select kernel for Gaussian Process?

In Gaussian Process (GP), the kernel (co-variance function) is used to measure the similarity between one point and a given point. There are so many kernel functions for GP, and I wonder how to select ...
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175 views

Random forest on multi-level/hierarchical-structured data

I am quite new to machine learning, CART-techniques and the like, and I hope my naivete isn't too obvious. How does Random Forest handle multi-level/hierarchical data structures (for example when ...
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81 views

What is the Probability Distribution of NLTK Naive Bayes?

As I know Naïve Bayes has various distributions, as said in Sci-kit learn manual: The different naive Bayes classifiers differ mainly by the assumptions they make regarding the distribution of ...
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26 views

Dummy Variables and Learning algorithms

Suppose a predictor variable $x$ is nominal/categorical with three levels: $1,2,3$. Thus we create two dummy variables $x_2$ and $x_3$ with level $1$ as the reference variable. Let $y$ be a binary ...
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1answer
123 views

Applying kernel function to input data before giving it to algorithm

I have gene expression data, I do dimensionality reduction and clustering with self organizing maps, but self organizing maps do not perform well with my data. I want to map my data to feature space ...
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13 views

Classification training dataset: which is the structure should have? [on hold]

I'd like to apply k-NN to the following dataset and I don't know if the training dataset structure is correct and fit correctly ...
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1answer
106 views

Stochastic Programming (e.g. LP) with MCMC

I have just started learning about MCMC (using PyMC), and it seems to be a hammer that can be used to solve a large class of inference and optimization problems. While I understand that there are ...
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26 views

Machine Learning Process for detecting edges of overlapping objects with OpenCV

I'm quite new to machine learning and a bit unsure about the whole process and the interpretation of the results. The Task: I have images with some objects of somewhat the same color and shape which ...
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30 views
+50

Expected required sample length to train a hidden Markov model

Say one wishes to train a hidden Markov model with $n$ hidden states, and (accidentally) the problem itself can be described with a hidden Markov model with $n$ (or less states). What is the expected ...
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29 views

Introduction to recurrent neural networks?

I have two questions: 1- What are the applications of recurrent neural networks? 2- Can you recommend some good resources/papers/tutorials that introduce recurrent neural networks?
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1answer
63 views

How can I evaluate the performance of a system that generates word clusters?

The word2vec tool uses deep learning to compute vector representations of words. They've mentioned that - "The word vectors can be also used for deriving word classes from huge data sets. This is ...
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1answer
42 views

Predict observation using Hidden Markov Models

I have a sequence of observations e.g. ["Click","Scroll","Hover","Zoom","Select"]. I need to predict the next value of this observation sequence but not the next hidden state. I know that there are ...
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1answer
21 views

full batch v.s. online learning v.s. mini batch

This is a question from a coursera course: Suppose we have a set of examples and Brian comes in and duplicates every example, then randomly reorders the examples. We now have twice as many examples, ...
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33 views

Difference between estimation and learning

What is the difference between parameter estimation which includes system identification and learning in machine learning perspective? Let say the model is y= Ax. x is the input and y is the output. ...
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308 views

How to combine the responses of two sensors?

I have two sets of responses from two different sensors. In each set, the first column is distance measured in feet, and the second column is the response of the sensor. Sensor A has response values ...
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9 views

Represents istances with multiple values for an attribute and similarity between them

In the scenario in which I'm working each entity could be represented in terms of ten distinct properties that I will call p1, p2, ..., pn. For each of them, an entity, can have its specific range of ...
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21 views

Minimizing the Training data

I have a grey-box model of the form Y= a + b X1 + c X2. Where a, b and c are the coefficients based on regression. The regression variables X1 and X2 are determined based on ...
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26 views

Conceptual question on optimization

What is the intuition and the physical meaning of the mathematical expression in convex optimization? When using optimization algorithms like particle swarm or genetic algorithm, do they have ...
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5 views

Design a feature with time and presence information

Context: I am working on a decision tree classifier, trying to classify businesses as to whether they are likely to have an event occur (default) in the next 90 days. One input I get is whether, and ...
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2answers
100 views

Heuristic Feature Selection for Gradient Boosting

I originally posted on Stack Overflow and was told to move it here. If I am trying to select from two different sets of features for a Gradient Boosting Machine, but I do not want to run through ...
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1answer
522 views

What is being learnt?

This may seem a trivial question but I have a fundamental problem in understanding learning. In supervised learning, given and input-output pair, what are we learning? Are we learning the inputs ...
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1answer
93 views

SVM primal formulation: does the constants constraint matter?

When finding the maximum margin separator in the primal form we have the quadratic program $$min\frac{1}{2}||\theta||^2$$ $$\text{ subject to: } y^{(t)}(\theta \cdot x^{(t)} + \theta_0) \geq 1, \ ...
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27 views

Anomaly detection of web browsing sequences

Please consider that I'm quite new to machine learning. I need to create models based on browsing patterns of web users and find deviations from that model. I'm using web server access log files. For ...
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4 views

Profile variable in collaborative filtering

I'm trying to create a recommendation system based on purchases. I did some tests and I found that for some groups of customers, the recommender works very well, but not for others. How can I ...
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1answer
99 views

Issue in training Hopfield network and convergence problem

I am learning how to use Hopfield Neural network as a context addressable memory. The objective is to obtain a fixed point of the network which indicates an equilibrium state. This state vector ...
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Basic idea of zero inflated two part models(hurdel) and application to big data (machine learning)

I'm currently working on the data which has 90% 0s in response variable. Based on my research, it seems zero inflated models could be a solution to this. However, while I was reading related ...
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140 views

Linear Regression Real Life Example

I am learning Machine Learning(Linear Regression) from Prof. Andrew's lecture. While listening when to use normal equation vs gradient descent, he says when our features number is very high(like 10E6) ...
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3answers
91 views

Implementing R Machine Learning Model in Real World

I've been able to create some successful R ML models using some of the popular machine learning algorithms. However, I'm not sure how to implement the model where the end users (technically ...
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6 views

Categorizing text into IPTC subjects

Does anyone know where I can find a corpus I can use to train a classifier into IPTC news categories (http://www.iptc.org/site/NewsCodes/) ? A google search was not very useful. Thank you
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18 views

The variance-covariance matrix of the least squares parameter estimatimation

I'm learning Linear Regression for Regression from "The Elements of Statistical Learning". Why The variance-covariance matrix of the least squares parameter estimates is easily derived( from(3.6) ...
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2answers
103 views

GA or ANN, and suggestions

I am working to approximate, to extrapolate rather, values of a function from a few known values. Here is what I have: Less than 100 known I/O pairs. A monotonously positive correlation.en Something ...
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10 views

Comparing learning algorithms

I know that you can compare learning algorithms based on their average cross-validation accuracy (e.g 10-fold, 10-repeated CV) and their test set accuracy. Suppose model 1 is a logistic regression ...
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32 views

Algorithm for online handwriting recognition

Is there any specific algorithm for online handwriting recognition? The algorithm should recognize non-cursive and cursive handwriting. I know there is already a similar post on stackoverflow.com, ...
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3answers
572 views

How do you report percentage accuracy for glmnet logistic regression?

I am using glmnet where my dependent variable is binary (class 0, class 1). I want to report percentage accuracy of the model. So I use the ...
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1answer
54 views

Handling Missing Values During Test Phase

I was searching for methods for handling missing values in case of Regression task. There are already few threads but I couldn't find what I was looking for. Suppose I have 4 independent categorical ...
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18 views

How to understand kernel functions and how to choose a suitable kernel?

I am trying to describe my understand of kernels in the Support Vector Machine(SVM) and why some of them are more popular, but I am not sure if I misunderstand these concepts: 1) There are a large ...
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56 views

ROC vs. Accuracy [duplicate]

If you want to compare two learning algorithms, which metric is better to use in general: ROC or accuracy? I understand that in ROC, you get both the sensitivity and specificity?
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17 views

MDP value iteration

In Markov decision processes, what is the guarantee that value iteration chooses the same policy action from a given state for every iteration? I am referring to the slides given by AWM at ...
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1answer
121 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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18 views

Statistical Methods for Calculating Vending Machine Refill

Am looking into statics to help support a project I am undertaking. The project scope concerns intelligent replenishment / refill of vending machines. During an onsite service, a technician must ...