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

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Combining CostSensitiveClassifer with MultiClassClassifier [RWeka]

this is my first attempt at posting here. I looked through CrossValidated and found two similar problems without answers (see How to combine WEKA classifiers and Combine MultiClassClassifier and ...
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1answer
13 views

Solving feature bias issues in Learning to Rank with implicit feedback

I have a learning to rank system where implicit feedback (from user clicks) is used to determine +ve and -ve examples for the training. The problem is that (obviously) the learner sees only the top ...
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24 views

Matrix completion approaches for healthcare big data

I am working on a prediction problem that leverage sparse clinical datasets. Missing data rate is in the range of 80%. 1- I am wondering if there is any example of application of matrix completion ...
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17 views

Good way to use adaptive learning rates in neural network

Adaptive learning rates means using different learning rate for different weight in neural network. Except for the emperical method which updates these learning rates based on consistency in gradient, ...
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2answers
55 views

Use of nested cross-validation

Scikit Learn's page on Model Selection mentions the use of nested cross-validation: ...
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1answer
36 views

Random forest ML algorithm suitable for use on cluster based HPC?

I have developed a script using pythons scipy package to analyse a rather large model that I wish to solve, the model contains over 12gb of data, including over 500 parameters. Now running small ...
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1answer
46 views

Reverse AUC interpretation

Given a classifier (SVM) classifying in 2 'classes' (+1 or -1) for prediction purposes. It has an AUC score of 0.28, meaning its success rate is lower than just random predictions. If I just do the ...
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1answer
79 views

Machine-Learning algorithms for Forecasting

For work, I'm working on an app where you essentially forecast the failure rate of the overall machine through different factors such as the historical failure rates for the components used to build ...
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12 views

Treating numerals/cardinals in Bag of Words (BOW) model

I wish to do topic modeling on text corpus some of which are about company earnings which has lots of numbers in it. It has no sentence structure. I think tagging numbers using nltk.pos_tagging can ...
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28 views

Random Forest regression model in R and data overfitting

I have trained my random forest model on a 74,000 training examples where each example consists of two proteins Amino Acids sequence (20 characters) and some numeric values representing the similarity ...
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32 views

What does it take to learn a Model?

In Machine Learning, there are various models. I tried to learn few probabilistic models of Machine Learning. I read the theory, worked on problems and tested my results and could analyze my data ...
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23 views

Cross validation and accuracy calculation in lib-linear

I have two questions related to cross validation in LIBLINEAR I have 1000 documents from which i take 300 documents for training and rest 700 for classification . I train 300 documents with ...
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59 views

Generalized linear model with lasso regularization for continuous non-negative response

I have a big data problem with a large number of predictors and a non-negative response (time until inspection). For a full model I would use a glm with Gamma distributed response (link="log"). ...
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46 views

Online model training in R, without a static data

Let's say I have a model in R, a regression tree created by "glm",using "data1" dataframe: Model1 = glm(DepVar ~ . ,data=data1,family="binomial") Is there a way ...
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1answer
45 views

Selecting number of clustering classes automatically

I am working in text clustering. I would like to find a way to identify the number of classes for the clustering process automatically rather than proving the number of class manually. Is their any ...
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1answer
54 views

How to construct a reasonable prior and likelihood for Bayes modelling?

To apply Bayes inference for data analysis or machine learning, we have to construct prior and likelihood, right? But if I fail to come up with a reasonable prior and likelihood, then the Bayes model ...
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2answers
105 views

Machine learning algorithms to handle missing data

Am trying to develop a predictive model using high-dimensional clinical data including laboratory values. The data space is sparse with 5k samples and 200 variables. The idea is to rank the variables ...
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15 views

Computing directly comparable wavelet features on variable-length training examples

Consider a classification problem in which the raw data are snippets of a larger 1-D time series signal. In my application, the signal is the response of a motion sensor as a function of time (the raw ...
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2answers
87 views

How to find optimal values for the tuning parameters in boosting trees ?

I realise that there are 3 tuning parameters in the boosting trees model, i.e. the number of trees (number of iterations) shrinkage parameter number of splits (size of each constituent trees) My ...
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11 views

Heuristics for unsupervised or semi-supervised approaches to GIS coordinate data

I have a more conceptual/heuristic question about how to go about formulating a problem in order to take a semi- or unsupervised method of solving it. I'm working on a project with data collected ...
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1answer
56 views

Classifier vs model vs estimator

What is the difference between a classifier, model and estimator? From what I can tell: an estimator is a predictor found from regression algorithm a classifier is a predictor found from a ...
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9 views

Detecting/recognizing landscape and architecture photographs

I have a large set of photos of various kinds, labeled with some tags but the tags cannot really be trusted (e.g., some portraits will have a tag 'portrait' while many won't, likewise for 'landscape', ...
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10 views

In RVM, is the kernel allowed to depend on the full dataset?

I want to use Relevance Vector Machines and need to define my custom made kernel. I was wondering if it is allowed for the kernel to depend on the full dataset. For exampe, I can calculate a certain ...
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28 views

How do i estimate the Weights of the predictions assigned to each of the tree in GBM using R? How does GBM split nodes?

I ran a GBM model in R with loss function as bernoulli and n.trees=1000. I want to see the weights assigned to the predictions coming from 1000 trees. Is there any command in R that does that? How ...
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23 views

Item Response Theory alternatives

What are other approaches than Item Response Theory to model learning of students in standardised tests?
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5 views

Fast procedurally built inverse model

Suppose I have a DB into which the following key values are entered (in that "random" sequence) {16, 32, 256, 2, 8, 64, 4, 1, 128, 512} Assuming the values get ...
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1answer
38 views

Getting a probibility from a Normal distribution

I'm reading a blog about Thompson Sampling, and I'm having some trouble understanding some statistical concepts. I believe I understand when the author says $$ p(\mu_a \mid \mbox{data}_a) = ...
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9 views

Transition matrix in left-right hidden semi-Markov model

i'm developing a hidden semi-Markov model left-right . In a left-right model a sequence of $M$ states starts in state 1 and ends in state M, with no repetition of states. Since the model is ...
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104 views

Complete machine learning library for Java/Scala

Python is plenty of ML libraries (like the great scikit-learn). Is there any good for java/scala, containing many algos (regression, classification, clustering, cross-validation, feature processing), ...
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19 views

Sparse ELM vs SVM

What's the difference between SVM and Sparse Extreme Learning Machine with Gaussian kernel proposed in the following paper:http://www.ntu.edu.sg/home/egbhuang/pdf/Sparse-ELM-IEEE-T-Cybernetics.pdf As ...
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14 views

Censored data when censoring time is uneven

I have a data set relating to credit defaults. The data set contains around 100 predictors (some categorical and some numeric). I am interested in predicting the time to default, if the person ever ...
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13 views

Goodness of fit of an approximation of a PDF

I'd like to evaluate the performance of an algorithm which learns to approximate a discrete PDF for a latent variable given some noisy input. Now, is there a standard test to evaluate the goodness of ...
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30 views

What are the mathematics I need to learn, before I start research in data mining [duplicate]

I usually use text mining, graph mining, Information retrieval, and natural lanuage processing. Also i will use the fundamental concepts of data mining like classification, association and clustering. ...
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56 views

What should I use - Multi label classification or Multi class classification?

In my dataset, I have 2 labels, positive and negative. Most samples belong to only one class, either positive or negative. A small fraction of samples take both labels i.e. both positive and negative. ...
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22 views

BOW prediction of cluster for training data

I am creating a bag of visual words for classification of videos. I am not using SURF descriptors and that is why I couldn't use OpenCV's BOWImgDescriptorExtractor ...
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20 views

Reference Request: Regularization

Lately, a wealth of regularizers have come into being. The area of model selection has generated a great amount of interest. Many times, we would like to control the complexity of the model, but do so ...
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19 views

Importance of Time Features

if you have a time series and you want to do some predictions, what time feature should you use ? lets say we are trying to predict how many people visit a certain website, we have data for the ...
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27 views

How to handle the error of glmnet package for non-positive lambda?

I'm using glmnet package to learn regression models,it works fine, but for some models, I face an error and my script stops running. Here is my effort: ...
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2answers
54 views

Cluster Data based on Distribution

I have a list of diseases for my research. For each disease, I have a list of ages for the diseases. "Breast Carcinoma" may be a list of [1,2,2,3,4,5,5,5,5,5] while "Adrenal Cortex Neoplasms" maybe be ...
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1answer
57 views

Is there a decision-tree-like algorithm for unsupervised clustering?

I have a dataset consists of 5 features : A, B, C, D, E. They are all numeric values. Instead of doing a density-based clustering, what I want to do is to cluster the data in a decision-tree-like ...
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1answer
39 views

Having a Neural Network recreate what it's learned

I've created a basic Neural Network that learns from basic information and can verify whether or not a piece of information matches it's parameters from a match percentage. Conceptually however, I ...
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1answer
47 views

Comparing topic distributions between corpora using Latent Dirichlet Allocation and R topicmodels or python gensim

So I am working on a problem where I want to extract a set of LDA topics from one corpus, and then compare the distribution of those topics in other corpora. So basically I want to lock-in the topics ...
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1answer
44 views

Machine Learning on Percent/Continous Dependent Variable

I have a large dataset of 30,000 cases with 150 variables. I am looking for a few possible machine learning solutions/methods that I could try and use for cross validation. My dependent variable ...
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20 views

Association Rules “with a kind of class”

I want to use/adapt a recommendation algorithm for posters in an e-commerce. The thing is that I want to use previous categories searched before posting in a particular category (has to be at a very ...
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29 views

Machine learning with weighted / complex survey data

I have worked a lot with various nationally representative data. These data sources have a complex survey design, so the analysis requires the specification of stratification and weight variables. ...
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13 views

LMS cost function vs cross entropy cost function in neural networks

What is difference between using various cost functions: LMS,Cross entropy in neural networks? All of them have same derivative w.r.t final activation and hence all the gradients are still gonna ...
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3answers
78 views

What is shallow architecture in machine learning?

What is a precise definition of shallow architecture in machine learning?
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1answer
110 views

Intuitive explanation of Bayesian logistic regression?

I'm looking for an intuitive explanation of Bayesian Logistic Regression (I'm using it for texts if that's relevant). It seems that this article presents it, but it's, uh, way too mathy. Thanks!
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2answers
138 views

Why does PCA maximize variance of the projection?

Christopher Bishop writes in his book (Pattern Recognition and Machine Learning) a proof, that each consecutive principal component maximizes the variance of the projection to one dimension, after the ...