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

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Understanding and Implementing a Dirichlet Process model

I am trying to implement and learn a Dirichlet Process to cluster my data (or as machine learning people speak, estimate the density). I read a lot of paper in the topic and sort of got the idea. ...
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17 views

What is data augmented by the additive inverse?

I am reading Biclustering of expression data (Cheng and Church, 2000) The paper is about the Cheng and Church biclustering algorithm and its main metric, the mean squared residue (MSR). It is said ...
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What sort of feedback button should I implement to measure the difficulty of a task

---background info--- My company has built a Search Engine Optimisation product that can suggest monthly prioritised SEO activities (task suggestions), that will have the most benefit to the end user. ...
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29 views

Converting a similarity to a dissimilarity [duplicate]

I am working on a clustering problem for which I have to manually choose the number of clusters. I have a visualization tool that helps me decide whether the clusters are good. In order to ...
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1answer
30 views

Can a deep belief network (stacked RBMS) be used solely as a dataset generator?

I have a large dataset (tens of thousands of predictors) on which I would like to perform feature reduction with the intent of better model-building for prediction. Deep Belief Networks seem to ...
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22 views

What is a shift bicluster?

I am reading A comparative analysis of biclustering algorithms for gene expression data (Eren, Kemal, et al. - 2013) When explaining the Cheng and Church method, it says that: MSR was shown to be ...
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2answers
44 views

Splitting an imbalanced dataset for training and testing

I have a highly imbalanced dataset. My question is how to split the dataset for training and testing? I want to have a separate training set and a separate testing set. One idea I had is just to ...
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3answers
97 views

The value of adding the ROC graph if the AUC is given

I always see in papers that when they want to show how they classifiers performed, they provide ROC graph and the AUC score. Now as far as I know only the AUC tells how well the classifier performed, ...
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42 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of ...
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198 views

What is the right attitude toward open source machine learning toolkits?

There are lots of machine learning toolkits nowadays, such as weka, sklearn, R libs. If we choose to use these toolkits, besides that it is convenient, sometimes ...
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51 views

How to perform parameters tuning for machine learning?

I have a very basic question regarding parameter tuning using grid search. Typically some machine learning methods have parameters that need to be tuned using grid search. For example, in the ...
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48 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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49 views

Imbalanced training dataset and Random Forest regression model

I have a large dataset (>300,000 observations) that represent the distance (RMSD) between proteins. I'm building a regression model (Random Forest) that is supposed to predict the distance between any ...
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16 views

Difference between summing and multiplying covariance matrices?

Say we have an RBF covariance matrix A and some periodic covariance matrix B for a given dataset. Covariance matrix A says that you believe that points that are close together are somewhat similar, ...
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15 views

Which approaches are known to extract product / service data from previously unknown webpages via machine-learning?

To avoid reinventing the wheel, which approaches are known to extract product / service data from previously unknown webpages via machine-learning? Which keywords in a search engine might give me ...
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36 views

Precision and recall Break-Even performance

I am using WEKA to do classification. I wish to compare with an existing paper that uses the Precision and Recall Break-Even performance as their results. Can someone please help in order for me to ...
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36 views

anomaly detection on logs data

I wonder , if someone know the open source anomaly detection algorithm on computer log ? For an example , computer log look like as mentioned below : "value UL-CCCH-Message ::= { integrityCheckInfo { ...
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1answer
13 views

feature representation for DNA bases classification

I'm currently dealing with large DNA sequences for machine learning purposes, I'm basically improving existing methods. What I have is several millions of DNA sequences : ACGTAGGCAGGCTTTC ... In ...
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28 views

Vector Quantization of heavy tailed distribution

I'm generating with Monte Carlo simulation some stock price $X$. Once I have the stock price sample, I want to cluster it with 100 points $\hat{X}$. My problem is that the error associate with my ...
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2answers
59 views

Do discriminative models overfit more than generative models?

In an interview, the interviewer said that discriminative models tend to overfit more than generative models because they solve a more complex problem and hence consume more resources (or parameters) ...
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22 views

What to do for Dirichlet distribution when elements of X vector may be zero

So I want to define a Dirichlet distribution over frequency vectors which are unit vectors whose elements represent the frequency with which different characters occur in a body of text. Trouble is ...
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1answer
24 views

Data Conversion to Standard data format in hierarchical Dirichlet process

I'm trying to test the performance of posterior inference on a set of documents with hierarchical Dirichlet process for topic modeling. How can i convert my data (document) to standard data format ...
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1answer
24 views

Offline training or batch wise training

Can somebody please explain how to train a neural network in batch mode. I have a single target time series of length $N$ for a given input time series of the same length. In order to apply Hopfield ...
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1answer
31 views

Grid Search for hyperparameter and feature selection

So I need to select my hyperparameters and also my features. A full grid search of the space of hyperparameters and features is too computationally intensive, so what I am doing instead is for each ...
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25 views

How to determine appropriate number of features and also which features to select?

So I have a dataset which I am using K fold cross validation on to select the number of features and which features should be selected. As I understand it, I would set the number of features to be ...
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26 views

How to build feature vectors from profile data

I want to build feature vectors from data of my test set, which contains profiles of people. I always want to compare two profiles to each other. Thus my features are: - Same surname ∈ {undefined, ...
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1answer
27 views

Ploting classifiers' performance results for different datasets

I have five different data sets, and I applied five classifiers. I have also five performance evaluation metrics: precision, recall, F-measure, Accuracy, and AU-ROC. Is there any good plot that I can ...
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1answer
43 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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81 views

Machine learning techniques for spam detection, and in general for text classification

I am going to configure a system for spam detection. What I have is a dataset of labeled (spam/not-spam) strings containing, mostly, sentences. I have a background in machine learning techniques, but ...
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31 views

Why are after training 5-state HMM only few entries of transition matrix left greater than zero?

I try to create the speech recognition system based on 5-state HMM + Multivariate Gaussian function. I use my own feature vector derived from MFCC (Mel-frequency cepstral coefficients). The problem is ...
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16 views

Posterior distribution for LDA and Newdata

I am using the 'topicmodels' package in R. I tested the posteriori probability for newdata over jss_LDA result by this code : ...
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1answer
27 views

One vs All and One vs one in svm?

What is the different between onee vs all and one vs one SVM classifier?? Is One vs All mean = 1 classifier to classify all types /categories of the new image and one vs one mean= each type /category ...
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1answer
114 views

When is a proper scoring rule a better estimate of generalization in a classification setting?

A typical approach to solving a classification problem is to identify a class of candidate models, and then perform model selection using some procedure like cross validation. Typically one selects ...
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19 views

Converting FuzzykMeans to SphericalFuzzyKMeans?

I grabbed an implementation of FuzzyKMeans (FuzzyCMeans) from the nightly build of the Apache Commons Math library, but I now realize I need to use Cosine Similarity instead of the Euclidean Distance. ...
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18 views

Q-Learning: Can you move backwards?

I'm looking over a sample exam and there is a question on Q-learning, I have included it below. In the 3rd step, how come the action taken is 'right' rather than 'up' (back to A2). It appears the Q ...
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1answer
39 views

Automatic labeling of training set

I have once meet the following question, given a training set, is that possible to do the automatic labelling? In addition, if this training set consists of plain text files, is that possible to know ...
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1answer
34 views

In decision tree construction, can a good splitter have low information gain?

I have a data set with a candidate splitter variable that is a natural choice from the business perspective. It has two values, and the distributions of the target when conditioned on the two values ...
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1answer
54 views

How to interpret the number of k in k-nearest-neighbour classifier?

I have done some classification work using a k-nearest-neighbour classifier (kNN). And the classification performance is evaluated using cross-validation method. Some testing code from Matlab Help are ...
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2answers
317 views

How can stochastic gradient descent avoid the problem of a local minimum?

I know that stochastic gradient descent has random behavior, but I don't know why. Is there any explanation about this?
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18 views

Cross validation training support vector machine

Can somebody explain me how to perform cross validation while training Support vector machine via some example?
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28 views

What is the meaning of the term “enrichment” when performing cross-validation?

Trying to understand a discussion of a 5-fold cross-validation process to validate a predictive model and its results, there is a particular phrase which has me stumped, i.e.: The predictions of ...
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2answers
54 views

Area under the ROC curve or area under the PR curve for imbalanced data?

I have some doubts about which performance measure to use, area under the ROC curve (TPR as a function of FPR) or area under the precision-recall curve (precision as a function of recall). My data is ...
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10 views

Dictionary matrix for online sparse coding doesn't learn [migrated]

Following Online Dictionary Learning for Sparse Coding and using an inference function I've found on the Stanford's website, I'm trying to online learn a Dictionary matrix. Tested both on resized ...
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2answers
133 views

The difference of kernels in SVM?

Can someone please tell me the difference between the kernels in SVM: Linear Polynomial Gaussian (RBF) Sigmoid Because as we know that kernel is used to mapped our input space into high ...
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1answer
52 views

What kind of model is used by 20 Questions?

Which kind of machine learning concept / model is used in 20 Questions? Is this kind of thing best solved by a neural network? Where I can read something about it?
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3answers
240 views

Why is AUC higher for a classifier that is less accurate than for one that is more accurate?

I have two classifiers A: naive Bayesian network B: tree (singly-connected) Bayesian network In terms of accuracy and other measures, A performs comparatively worse than B. However, when I use the ...
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1answer
66 views

SVM basic theory?

I have some questions about SVM: In SVM there is a nonlinear and linear SVM. What is the difference between them? To do classification in SVM, we will find the linearly separable boundary ...
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1answer
39 views

Is the value of $\alpha$ the same for all support vectors (SV) in the dual and what is the reason for it if they do or don't?

Consider the dual with no offset and not slack. In the dual we have that for data points that are support vectors: $$\alpha_t > 0$$ and that the constraint is satisfied with equality (since a ...
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1answer
25 views

Different formulations for SVM with slack variables (primal)

I have seen two different ways to formulate the SVM optimization but I was not sure what the difference was between them or if there was any difference. First formulation: $$min ...