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

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4answers
529 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
61 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
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0answers
77 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
43 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
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0answers
24 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
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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
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2answers
71 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
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2answers
186 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
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1answer
134 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
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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
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2answers
50 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
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0answers
27 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
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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
141 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
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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 ...
1
vote
1answer
41 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
31 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
63 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
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0answers
27 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
46 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
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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
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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
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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 ...
0
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1answer
42 views

How to define silhouette for one cluster?

I want to compare two clustering algorithms. I took data that the first algorithm gathered in one cluster. The second algorithm gave 3 clusters for the same points. In order to compare the results, I ...
3
votes
2answers
124 views

k folds cross validation on a multi-class dataset

Cross validation is one of the most important tools because it gives us an honest assessment of the true accuracy of our system. In other words, the cross-validation process provides a much more ...
0
votes
3answers
92 views

Scalability of Markov Clustering

I want to do graph clustering on a large dataset (A graph with 600,000 Nodes and tens of millions of edges). I read about Markov clustering. I saw this algorithm involved the calculation of a ...
-2
votes
1answer
44 views

k-medoids algorithm with incomplete distance matrix

I want to apply k-medoids algorithm using an incomplete distance matrix as input. How can I handle the lack of information of this matrix? Just ignoring the missing distances? Or is there a better ...
1
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1answer
34 views

k-core clustering algorithm

I am trying to cluster data. Each point in this dataset is connected to some other points. I want to define clusters "depending on how much the points are connected to each other". After some ...
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0answers
14 views

What is the latent class in pLSA

I want to implement Probabilistic Latent Semantic Analysis(pLSA) in Python. I have searched many times but couldn't find a simple tutorial. ...
0
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0answers
31 views

What can be a cause of a extremely high standard coefficient?

I am using RapidMiner to perform linear regression with ridge parameter 1$\text{E}$ -8, min tolerance 0.05 and M5 prime for feature elimination. The std coefficient ...
0
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0answers
21 views

Correlating ranked lists

Let's assume I have 10 users who rank a list by preference. A B C etc. My questions are: What is the best statistical method to find which lists are the most correlated? If they are the same, ...
2
votes
1answer
54 views

How to set the step size for stochastic gradient descent such that its provable it will converge

Recall stochastic gradient descent (for regression): $\theta = 0 $ $ \text{Randomly select } t \in [1,n]\{\\ \quad \theta^{(k+1)} = \theta^{k} + \eta_{k}(y^{(t)} - \theta \cdot x^{(t)})x^{(t)}\\ ...
7
votes
1answer
81 views

Linear regression closed form solution and having enough training points

I was trying to understand better when we can learn a unique parameter for linear regression and how much data is required to get one. Say that we want to learn a parameter $\theta$ such that ...
3
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0answers
36 views

Machine learning with ordered labels

The usual method for adapting binary classifiers like various SVMs to multilabel data is one-vs-all, which assumes that labels are independent and in case of a prediction error we don't care what ...
1
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0answers
34 views

Random initialization with k-means clustering

I read on my machine learning course (on coursera) that random initialization performed several times and then taking the cluster with the lowest cose could help when the number of clusters is ...
0
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0answers
25 views

Test data has maximum number of unseen nGrams and prediction is failing

I have built a Machine learning model for twitter sentiment analysis. I have followed following steps to build my final model. Model Creation: collected uni-bi-tri grams from entire training data ...
1
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0answers
31 views

What does the term “Estimation error” mean?

I was reading some notes on machine learning when I came across the following sentence: First, we may have a large estimation error. This means that, even if the true relationship between x and ...
3
votes
1answer
65 views

Do fewer support vectors imply a simpler model?

I am applying $\epsilon$- and $\nu$-regression to sample data, and I discovered I had different results in terms of the count of support vectors. When I have fewer support vectors, does it mean that ...
0
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0answers
26 views

Evaluate collisions in classification problems

Short Introduction In a classification problem, the objective is to identify to which of a set of categories a new observation belongs, on the basis of a set of examples whose category membership is ...
2
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3answers
90 views

Performing PCA with only a distance matrix

I want to cluster a massive dataset for which I have only the pairwise distances. I implemented a k-medoids algorithm, but it's taking too long to run so I would like to start by reducing the ...
3
votes
0answers
62 views

Evaluating a regression model's performance using training and test sets?

I often hear about evaluating a classification model's performance by holding out the test set and training a model on the training set. Then creating 2 vectors, one for the predicted values and one ...
0
votes
1answer
116 views

Multidimensional scaling using Python

I have 6,000 points for which I have all pairwise distances in a distance matrix. I want to get an idea whether these data were generated by a mixture of Gaussian distributions so I'm trying to get a ...
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0answers
37 views

How to extract structured information from a text string?

I have a text string containing unstructured data and I would like to analyze it in order to extract structured information. In particular, this text string specifies when a service is operational ...