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

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4
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1answer
128 views

Bayesian MLPs using the MCMC methods - any tricks of the trade?

Having used the NETLAB library for MATLAB to implement Bayesian Multi-Layer Perceptron (MLP) neural networks using MacKay's evidence framework, I am now experimenting with Markov Chain Monte Carlo ...
1
vote
1answer
35 views

How to initiate bias node in a restricted Boltzman machine

I am new to Neural Networks and trying to implement RBM. I am stuck on initializing the visible layer's bias value. Is it supposed to initialize to some random number or there is some probabilistic ...
0
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0answers
34 views

Supervised or unsupervised learning problem?

currently I'm working a pattern recognition problem. I have been using supervised learning (neural network and svm with one class classification) but I think I'm doing it in a wrong way. For ...
0
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1answer
24 views

Supervised learning based on phase space representation

Phase space learning Paper1 and Paper2 in neural network represents the input in higher dimension in auto associative learning. So, the network functions as an auto-associative memory where dynamical ...
1
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0answers
31 views

Sizing of training and validation sets in machine learning: Is there a proven optimum, or merely heuristics?

When I watch presentations where machine learning algorithms were used, the amount of data put in the training and validation sets seems to be somewhat arbitrary. Sometimes it's 80-20, sometimes it's ...
0
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0answers
18 views

Using LDA in non-realtime twitter data

I try to understand user characterization from twitter data. How can I understand the user's interest from statuses? From my researches, LDA(Latent Dirichlet Allocation)suitable for topic extraction. ...
0
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0answers
14 views

Reference Request: Human speech extraction using Machine Learning

I am trying to extract human voice from a noisy clip and studied some test upon it like, voice clipping using deep learning or MLP ann etc., then speech identification using a sequence based ...
0
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0answers
19 views

Segmenting an interval sensibly

Is there a canonical/recommended approach to or algorithm for splitting up an interval with the intent of minimizing the number of segments while keeping a high accuracy? It is essentially an ...
0
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0answers
18 views

Need subspace partition algorithm, not necessarily a full classifier

The image above represents a hypothetical data set of interest. For some set of points in N-dimensional space (each attribute of the data set corresponds to one dimension), I want to identify ...
0
votes
1answer
23 views

Statistic test on percentage correct classified by emotion recognition

For a potential emotion recognition bachelor-project I was wondering what statistical test I have to perform when I get my results to test whether it's significant. I will be testing which combination ...
0
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0answers
16 views

Low accuracy for training in image classification

I'm a newbie using LinearSVM to train the classifier. I labelled the images of 'buildings' as 1 and the others as -1. The training result is as follows : and As you can see in the image some of ...
1
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0answers
26 views

Possible classification techniques to use when each feature is a probability distribution

I am working with some data where the features have a temporal aspect (e.g. how often does a feature occur between $t_{begin}$ and $t_{end}$). I am trying to build a binary classifier for this data. ...
0
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1answer
67 views

Good algorithms for feature extraction from images?

I am searching for some algorithms for feature extraction from images which I want to classify using machine learning . I have heard only about [scale-invariant feature transform][1] (SIFT), I have ...
0
votes
1answer
47 views

When to use accuracy and precision to evaluate binary classifiers?

I came a cross two ways to evaluate the performance of binary classifiers: accuracy and precision. When to choose each? And what are the advantages and disadvantages of each one?
2
votes
1answer
57 views

Deriving $\beta$ from expected loss function (Hastie, Tibshirani)

I am looking at equation (2.16) from Elements of Statistical Learning and can't seem to be able to derive it. I used $f(x) = x^T\beta$ as the linear model, and tried calculating $\beta$ by minimizing ...
1
vote
3answers
188 views

Evaluating a regression model

For classification problems I have been using Neural Networks and measuring Type I and II error using the confusion matrix and its measures as per this resource which is pretty straight forward. ...
2
votes
1answer
85 views

Run time analysis of the clustering algorithm (k-means)

I was reading some notes on ML and clustering and it claimed that the run time of clustering was O(kn) where k is the number of clusters and n is the number of points. I was wondering why this was ...
1
vote
0answers
23 views

Statistical testing: Multiple classifiers, 1 domain. Would rANOVA be appropriate?

When comparing the performance of two classifiers over a single domain, in the context of a classification problem in machine learning, it is common to use a paired t-test, using the 10 average ...
2
votes
1answer
103 views

Orthogonality in bias variance tradeoff

I have a function class $\mathcal{F}$. I get $n$ samples according to a model $$y = f^*(x)+\epsilon$$ I find the best $\hat{f}$ from these training samples i.e. $$\hat{f} = \arg\min\limits_{f\in ...
2
votes
4answers
520 views

Hints on this computer vision / machine learning problem

I've been working for a while on a pet problem. The task is to identify and segment out the dark lines and possibly the wiggly ones too. I'm not looking for anyone to solve this problem for me...I'm ...
3
votes
0answers
44 views

How to perform hypothesis testing for comparing different classifiers

I am trying to classify a small dataset (around 500 records) into two classes. I used various methods like SVM, Naive Bayes and k-nn classifier. Now, I would like to set the results from one of the ...
2
votes
1answer
60 views

Evaluating the clustering of a Kohonen UMatrix

Given a converged Kohonen feature map, how would one evaluate the clustering in terms of intra- and inter-cluster distances? Assuming that both the trained codebook vectors and Unified Distance ...
1
vote
0answers
70 views

How do I implement a deep autoencoder

I'm trying to replicate results of this paper using Theano. The problem at the moment is, all Theano-related tutorials are only for MNIST classifiers, which isn't much use in unsupervised image ...
3
votes
1answer
42 views

Why the trees generated via bagging are identically distributed?

I have problem in intuitive understanding of following arguement: "The trees generated via bagging are identically distributed, thus the expectation of the average of a set of trees is the same as ...
0
votes
0answers
22 views

Tuning the inflation parameter in mcl

I read on the mcl documentation that the inflation parameter can be used to tune the granularity of the clusters. I am not very familiar with graph theory. What is the granularity of the clusters? Can ...
0
votes
1answer
33 views

Forcing a particular false positives rate in a learning algorithm

I have a learning algorithm that classifies points as 0 or 1 (haven't settled on which one to implement yet). Of the points I classify as 1, I want to ensure that the number of points correctly ...
1
vote
2answers
70 views

Dataset and papers for baseline [closed]

I'm doing a project about Topic Detection and Tracking in text. I need to perform a baseline so I can compare existing results with mine. I read some papers where they use datasets that are not so ...
2
votes
2answers
181 views

How to create ROC curve to assess the performance of regression models?

I knew that, ROC curve are use to assess the performance of classifiers. But is it possible to generate ROC curve for the regression model? If yes, How?
0
votes
1answer
117 views

One class classification with libsvm. Accuracy results in 0%

A quick recap for what I want to do, I want to determine if a text is written by the same author or not. Thus I use one-class classification. In my training set (18 samples), it looks like this (for ...
1
vote
0answers
16 views

Admissibility and domination for estimators

Watching a video by the "mathematicalmonk" on the web, I was wondering how to answer this kind of questions: Given $X_1,\ldots,X_n\sim \mathcal{N}\left(\mu,\sigma^2\right)$. Assume that $\mu$ is ...
0
votes
3answers
60 views

Converting a distance to a similarity

I am working on a graph clustering algorithm (mcl). It gives the opportunity to give weights to the edges. The weights must be similarities, but I have a distance. The values of this distance range ...
2
votes
2answers
96 views

Is “not-overfitting” a utopian scenario?

We say a model overfits when classification error increases on the test data. The reason behind this is that the training data is not a representative of the distribution from which data is sampled. ...
1
vote
2answers
49 views

Model instability in data mining. When it is big enough to discredit a model and how to measure it?

Let's say I have two models. One has cumulative lift on test data 4.322578, second 2.84488. The only advantage of the second over the first consists in the quality of having the cumulative lift curve ...
2
votes
0answers
26 views

Choice of an evaluation metric for a graph clustering algorithm

I have instances for which the only thing I know is 70% of the distance matrix. I know some of these points form groups of correlated points (each point of a group is "close" to every point of the ...
1
vote
0answers
40 views

Machine Learning : Classification algorithm for very high dimensional data which is uniquely definable in a very small sub-space

I am new to machine learning, so forgive me if i am doing something absolutely absurd. I have a classification task (~100 classes) and have about 2 million training data points in a 2000 dimensional ...
3
votes
1answer
33 views

gaussian mixture model - approximate a matrix

I have a similarity matrix M - the value M(i,j) indicates the similarity between two elements i and j. I want to approximate that matrix using a Gaussian Mixture model or I want to cluster that ...
2
votes
2answers
139 views

Using the gap statistic to compare algorithms

I want to compare the performances of two clustering algorithms that give me different numbers of clusters. I recently learned about the gap statistic. However, from what I have learned, this ...
1
vote
2answers
78 views

How to report a SVM model to a 3rd party after cross-validation?

I have a binary classification problem. I trained my dataset using a Support Vector Machine (SVM). Now I want to report the model I trained to a 3rd party so that they can use. For the primal probem ...
0
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0answers
20 views

difference between text classification and categorization

Could any one help me to clarify the exact difference between text classification and text categorization in machine learning point of view. Thanks
1
vote
1answer
40 views

General questions regarding text-classification

I'm new to Topic Models, Classification, etc… now I'm already a while doing a project and read a lot of research papers. My dataset consists out of short messages that are human-labeled. This is what ...
5
votes
2answers
319 views

Can machine learning find all sort of crazy connections?

If you try a real thoroughly won't a computer find all sort of silly patterns? Messages from ETs in the bible rainy Sundays in China or Australia -> the chances of your sport team win reading many ...
0
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0answers
30 views

Which algorithmic approach is best for this problem

I have a problem where I get data from 3 different sources s1, s2, s3, and I have the target (value). I might have missing values from some of the predictor variables at certain rows. This is the ...
4
votes
2answers
103 views

Maximize sum of f(x), where f(x) is unknown, but we learn as each x is chosen

Let's suppose that I have a function like below, but I don't know what it is. However, as I choose x, I know what corresponding ...
-1
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1answer
62 views

Journals in statistical learning / machine learning [closed]

Can you please name some major and minor journals publishing articles in the field of statistical learning / machine learning. regards Anthony
0
votes
0answers
22 views

Word Sense Disambiguation in Practice

I have a question that might seem very obvious but I don't really have a good answer for it. There are many algorithms out there that deal with word sense disambiguation but all of the ones that I ...
0
votes
2answers
45 views

Machine Learning with Skewed Classes in R

I am looking for some suggestions on what methods are appropriate for training a dataset with a high skew in the outcome classes. The ratio of Class 0: Class 1 is about 20:1 and I am looking to ...
0
votes
0answers
30 views

Which diffusion of latent Dirichlet allocation is helpful for assign the words corresponds to each topic?

In my corpus documents I have two different subjects. Which diffusion of LDA (asymmetric or symmetric) could help for assigning the words corresponds to Subject 1 and Subject 2 in my Topics? Here is ...
0
votes
2answers
86 views

Will Multivariate Gaussian classifier work for text classification?

So far i have evaluated mn Bayes and Bernoulli, so my question is if i take the counts of the words of each document and use them for assigning the document to the particular class will it work with ...
0
votes
1answer
29 views

Classifier weighted towards recall?

I have a classification problem where getting true positives is much more important than true negatives. To be clear, I know that roughly 10% of my population are actual positives, but I can assign ...
0
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0answers
18 views

What is the difference between the metric window width and Nearest-neighbor's window in Kernel Smoothing methods?

I'm learning Kernel smoothing methods. I didn't really get the difference between the metric window width and Nearest-neighbor's window. For me both seem the same. Can anybody explain it to me? for ...