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

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Machine learning - curve categorisation

I have curves of the following structure (it is the blue one I am interested in) These curves reflect the volume of blood (actually gamma ray counts) in the left ventricle as a function of time ...
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1answer
22 views

Statistical Commute Analysis in Java

I have a rather large commute every day - it ranges between about an hour and about an hour and half of driving. I have been tracking my driving times, and want to continue to do so. I am capturing ...
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18 views

How to best make millions of forecasts using time series data?

I need to quickly (within a few hours; running it every night) and accurately make roughly 50 million forecasts. The time series data is daily, hierarchical (about 50 million series at the bottom ...
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12 views

Feature/Variable selection to accompany mixed models?

I am trying to conduct an exploratory/data mining analysis to discover what socioeconomic factors best predict grade-school performance in children. I have a dataset with about 50000 ...
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11 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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1answer
36 views

Algorithm to find subsets with high correlation

I have a reasonably large dataset (d) with predictor variables x1...xn and a target variable y. I can use recursive partitioning (such as CART or rpart in R) to find subsets of d with a high (or low) ...
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7 views

Is it safe to mix different encodings of features in one data set

I'm investigating which feature encoding yields the best results for training a predictive model on a biological problem. All variables have the same format and possible values before conversion to ...
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7 views

VC-Dimension of n-node binary decision tree in N-dimension feature space

Given input feature space $\mathcal{X} =\{0, 1\}^N$ and output label space $\mathcal{Y}=\{0,1\}$ , prove that the VC-dimension of a binary decision tree with $n$ nodes is in $O(n\text{log}N)$. I've ...
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17 views

Working with few data examples

I have been asked often in some interview, that how we should proceed when we have less data examples(say 50 or 100). What considerations needs to be made while choosing any algorithm. few points ...
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1answer
13 views

How to improve the performance of K-nn algorithm in R?

I am having a digit recognizer data set which has column names as label, pixel0, pixel1...pixel783. pixel values vary from 0 to 255 indicating the lightness or darkness of that pixel, with higher ...
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20 views

How do the various distributions work into machine learning

I'm a student who recently started taking a machine learning course and I'm trying to understand how the various distributions fit into the whole thing. From the research I've been doing it seems the ...
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16 views

$\chi^2$ test vs F-test in feature selection

In the context of feature selection for classification, does it make sense to use one filter based on $\chi^2$ test and the other one based on F-test? Or they are "interchangeable"?
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9 views

cross validation for kmodes in r

I am using k-modes (link) from the KlaR library (link) to cluster text data. I am not sure how to determine predictive error and thus perform cross-validation. Here is the "toy" sample, lets use ...
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34 views

How to split a decision tree when information gains of all attributes are zero?

The textbook tells us that we should choose an attribute with the maximum information gain to split a decision tree. My question is what if all information gains are zero? Should we stop splitting or ...
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17 views

Numerical Problems in Mixture of Gaussians Classifications

I am doing two-class classification with Gaussian Mixture Models (GMMs). If I understand it correctly I have to build two models $p(x | C1)$ and $p(x | C1)$ for the probability of input $x$ given ...
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19 views

Best classifiers for large data sets?

I'm working on a data set that contains electricity consumption data. There will be 2-3 features used. I'm not sure if that is all of the features to be used. Also, it will be a really large data set. ...
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9 views

How do i generate variables that are relevant only for some classes?

I want to generate data for classification. I've generated data with 10 variables with two are relevant for all classes and 8 noise. now, I want to generate variables that are relevant just for some ...
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31 views

How to represent outliers for multi dimensional data (local outlier factor)

Below graph taken from http://en.wikipedia.org/wiki/Local_outlier_factor displays "LOF scores : LOF image : This is great for two dimensional data but what about data > than two dimensions. How ...
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2answers
28 views

Newbie: Decision Tree in R with Two classes(Yes/No) where one class (No) is much larger than other class (Yes)

I am trying to make a decision tree using 4 features (A,B,C,D) to predict an out come for two classes E(Yes, NO). The problem is that the number of observations in my dataset that belong to one class ...
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5 views

Sample weights for classification problems

How can certain samples in the training set be prioritized (given more weights) in classification problems? What is the formal methodology to do so?
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1answer
24 views

What kind of functions can have non whole degrees?

Thanks for the help in advance. I am reading a technical report on a regression algorithm that reports a pair of functions as having a total degree of freedom of 5.4. I believe that both of these ...
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1answer
28 views

Selecting most realistic C and g params after gridsearch

I just ran an extended SVC gridsearch in libsvm on about 9000 multi-dimensional vectors representing a time series. Here are the highest scoring results: ...
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1answer
45 views

How to evaluate a clustering/unsupervised learning problem with massive amounts of data, with labels only for a small fraction of points

I'm wondering if anybody can point me to work on the evaluation of unsupervised learning where there are a very large (say hundreds of millions) number of points and manual labelling can only ever be ...
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1answer
30 views

How to prove that the manifold assumption is correct?

In machine learning, it is often assumed that a data set lies on a smooth low-dimensional manifold (the manifold assumption), but is there any way to prove that assuming certain conditions are ...
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8 views

Unsupervised feature learning from raw text as a previous step for clasification?

I have a corpus of 2500 opinions, is it posible to use scikit´s restricted boltzmann machine implementation to extract a feature vector as a previous step to a classification task?. What aproach do i ...
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20 views

Hard Case - prediction of chain stores revenue

Data about average monthly revenue from 2000 stores around whole country. Gini coeff. of reve around 20%, with 50% of observation around average, very thin tails of distribution Explanatory ...
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15 views

mob model tree algorithm

I am trying to figure out the inner workings of the mob function in the party package. I can't figure out how the splitting variable is selected when it is a categorical variable. In the publications ...
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1answer
26 views

About grid search to find the best value of C

I know when I want to find the best values of C and gamma, I should use grid-search. But in my case I want to find just the best value of C. So, this is called a line-search. Is there any function ...
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38 views

Logistic Regression, SVM or NN?

Just attended Andrew Ng’s online course on ML and although I’ve understood the methods I seem to be missing the intuition on where to apply them in terms of classification problems. What are the ...
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19 views

How to compare traditional approaches with my approach?

The scenario: Consider that I have some 100 GB of raw data. When I extract features from it using the traditional, well-known approaches in my area, I get (say) 100,00,000 instances. When I build ...
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28 views

How to handle systematically missing values?

In my situation, one of two sources is not invoked if the confidence reported by the first source is higher than a threshold and hence it is missing in some examples. How can account for such missing ...
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1answer
14 views

Gaussian MRF/Markov Network: the zero precision = no connection?

Gaussian MRF in Gaussian information form: edge potential: $exp(\frac{-1}{2} y_s\Lambda_{st} y_t)$ node potential: $exp(\frac{-1}{2} y_t\Lambda_{t} y_t+\eta_ty_t)$ Why: precision parameter ...
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1answer
29 views

prediction of polls

Just as an example Scotland has poll to decide whether they need to be independent from UK or not. Here is BBC's summary of different polls: ...
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12 views

In Kneser-Ney smoothing, how are unseen words handled?

From what I have seen, the (second-order) Kneser-Ney smoothing formula is in some way or another given as $ \begin{align} P^2_{KN}(w_n|w_{n-1}) &= \frac{\max \left\{ C\left(w_{n-1}, w_n\right) - ...
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5 views

number of nodes in an unpruned decision tree

What is the number of nodes in an unpruned decision tree that is trained using n samples and that grows until there is only one sample in each leaf? I would like to know if there is a formula to ...
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0answers
16 views

Creating obligatory combinations of variables for drawing by random forest

Problem For my machine learning task, I create a set of predictors. Predictors come in "bundles" - multi-dimensional measurements (3 or 4 - dimensional in my case). The hole "bundle" makes sense ...
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21 views

Fusing probability scores from different independent sources

Consider a situation where two independent sources, $s_1$ and $s_2$ are giving probability estimates regarding the occurrence of a event $e$. I tried to model this as a bayesian network but that ...
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21 views

Open Source Machine Learning-Classification JAVA API's

Suggest some Open Source JAVA/C/C++ API's which has classification algorithms such as Decision Trees etc., Have tried out the following R,Weka,OpenNN,FANN.
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1answer
24 views

A/B split/bucket testing with three or more variants

Lets say I have three search engine e.g. search engine A, search engine B and search engine C. Each search engine is given a set of queries Q (e.g. apple,banana,carrot....), this set Q remains the ...
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1answer
13 views

Compare datasets from two machines [closed]

I have two data sets from two machines about their cpu, mem for n intervals of time. Machine 1 = [(cpu1, mem1), (cpu2, mem2), (cpu3, mem3), (cpu4, mem4), .... (cpuN, memN)] Machine 2 = [(cpu1, ...
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0answers
11 views

choosing best value for N when using N-Gram approach

the question is quite general, but I am doing a research related to supervised machine learning to classify two set of characters into two categories. in fact, I want to compute some measures of ...
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1answer
25 views

Cluster migration visualization

I have asked a very similar question at the Latex forum here, but in order to address the part of my question where I ask if there is a better way of visualizing the data I have, I wanted to cross ...
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0answers
14 views

GMM adaptation to new data [closed]

I have been using the GMM cluster package by Bouman, for which I did not find any adaptation module online. Before I start off reading up on the GMM adaptation theory and implementing it, I did like ...
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16 views

What book about use of machine learning in pharmacy would you recommend?

I know that machine learning is a very popular tool in pharmacy. Are there any books that describe use of machine learning in pharmacy?
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2answers
70 views

Newbie to neural networks

Just starting to play around with Neural Networks for fun after playing with some basic linear regression. I am an English teacher so don't have a math background and trying to read a book on this ...
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0answers
11 views

How to choose negative training sample for Classification problem

Choosing positives sample is a relative straightforward task, but I'm having some problem on determine what should I use for the negative example. I'm working on a SVM binary classificator, trying to ...
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0answers
22 views

Word probabilities in a Naive Bayes filter

While implementing a Naive Bayes filter, I stumbled across a problem with the calculation of the conditional probabilities $p(w|c)$ of a word $w \in \mathcal{W}$ given a class $c \in \mathcal{C}$. ...
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2answers
49 views

Random Forest proof notation

I am having a bit of difficulty understanding the notation in equation (1) on page 4 of the following paper: https://escholarship.org/uc/item/35x3v9t4#page-4 Specifically, what do $E_{X,Y}$ and ...
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1answer
46 views

What does correlated data mean and how can I visualize it with scatterplot?

I'm playing around with the Abalone dataset in R and following along with this article. The dataset has 8 variables that are taken into account to predict the number of ...
2
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1answer
37 views

What is meant by effective parameters in machine learning

My question might be a bit ambiguous, but I started to wonder what does the "effective parameters" mean in machine learning? I have heard few professors of machine learning in my university talk about ...