Questions tagged [machine-learning]

Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.

Filter by
Sorted by
Tagged with
2
votes
2answers
2k views

How can we find the decision boundary for two overlapping continuous uniform distribution?

Say I have $X \sim \text{CUnif}(a, b)$ and $Y \sim \text{CUnif}(c, d)$. The parameters of $X$ and $Y$ overlap i.e., $a < c < b < d$. How can I find a decision boundary in such case? I am ...
0
votes
1answer
521 views

Gradient boosting in R uses only a single variable

I am trying to build a boosting model using the package gbm in R. I have the following code: ...
2
votes
0answers
233 views

Nonnegativity of model optimism

The following sounds like a very basic question in learning theory to me, so I am hoping someone can point out the obvious. Efron's "expected optimism" is the expected difference between the ...
0
votes
1answer
4k views

Search in TF-IDF

I want to find the similarity between a document with documents coded as TF-IDF in a pickle file (Python). TF-IDF is done as offline so there is no problem, but when I send a new document for ...
1
vote
0answers
760 views

Incremental SVD in Collaborative Filtering

In the so-called incremental SVD used for collaborative filtering: http://www.machinelearning.org/proceedings/icml2007/papers/407.pdf http://www2.research.att.com/~volinsky/papers/ieeecomputer.pdf ...
1
vote
0answers
56 views

What is an 'atom' and what are 'atomic weights'?

I have come across the following statement: A notable feature of the Hierarchical Dirichlet Process is that all Dirichlet Processes' $G_j$ share the same set of atoms and only the atom weights ...
0
votes
1answer
1k views

Support Vectors Not Falling on Margin Lines for e1071 and kernlab packages in R?

In a previous thread, Computing the Decision Boundary of a linear SVM model(Computing the decision boundary of a linear SVM model), the following R code was given as a way to compute the formula of ...
3
votes
1answer
985 views

pLSA - Probabilistic Latent Semantic Analysis, how to choose topic number?

I am learning about pLSA (Probabilistic Latent Semantic Analysis) right now, in the hopes of being able to apply it to biomolecular annotation prediction. I have a very simple question: How do you ...
2
votes
0answers
791 views

Overlap in time series training sets

I have a time series prediction problem where the aim is to forecast the average value of $y_t$ over the next $T$ periods, given all the information available up to point $t$. For example, I want to ...
3
votes
1answer
165 views

How to classify data having sub-instance features?

I am trying to use machine learning on some peculiar (at least for me) data. Usually, when I do machine learning I am use to have the data in this format: ...
1
vote
1answer
65 views

Are MRFs with edges to all observed data possible?

I have been discussing the following issue with a colleague of mine and I can't seem to wrap my head around it. I have a computer vision background, so I'm mostly familiar with 2D MRFs/CRFs for image ...
3
votes
1answer
1k views

Entropy in decision tree classification

In the decision tree based classification technique. What is the difference among the different approaches like entropy, gini index? When to use entropy and when to use gini index?.
3
votes
1answer
351 views

How to find the input layer and the architecture for a Neural Network

I'm a software developer and I'll like to learn about neural networks. At this point I've find a problem which I'll like to solve at some point. It is about electrical load forecasting. I'm looking ...
1
vote
1answer
129 views

A question about the multistart heuristic and pseudo convergence

I'm teaching myself MCMC methods and I encountered this passage in a book that I am not able to make head or tails of: The phenomenon of pseudo-convergence has led many people to the idea of ...
8
votes
1answer
582 views

Why is the Dirichlet Process unsuitable for applications in Bayesian nonparametrics?

The discrete nature of the DP makes it unsuitable for general applications in Bayesian nonparametrics, but it is well suited for the problem of placing priors on mixture components in mixture modeling....
9
votes
1answer
14k views

Hidden Markov model for event prediction

Question: Is the set-up below a sensible implementation of a Hidden Markov model? I have a data set of 108,000 observations (taken over the course of 100 days) and ...
2
votes
1answer
262 views

How to determine if short strings of text are closely related to a larger text?

I have 1 short string of text (let's say it's a tweet, max 140 characters): "A review of my beloved Roku 3 media player" I also have a larger body of text (like a ...
2
votes
2answers
303 views

How would you frame this as a machine learning problem?

I have a trading software that buys and sells loans. There's an auction site where borrowers ask for some money and lenders bid on them until the borrower is fully funded and the auction ends. There's ...
1
vote
1answer
2k views

How would you use pair-wise plots to test the effectiveness of k-means clustering?

I am looking over slides for a big data class. The slides suggest doing a pairwise plot of data (if not too many variables) to evaluate the quality of output from k-means clustering -- with each data ...
0
votes
2answers
211 views

Machine learning algorithms/approaches for class recommendations?

I am asking a theoretical question about machine learning in terms of clustering. Is it possible, given a set of data of classes that students have taken in a semester to recommend additional classes ...
0
votes
2answers
71 views

Predictive algorithm validation

In putting a binary 1/0 predictive algorithm into production, what are the consequences where only the positive (1) predictions are checked, meaning only true or false positives are detected, and then ...
2
votes
1answer
352 views

Computing mutual information

I have a problem when computing the mutual information between two variables. Let's consider the following table: ...
14
votes
8answers
4k views

What are the “hot algorithms” for machine learning?

This is a naive question from someone starting to learn machine learning. I'm reading these days the book "Machine Learning: An algorithmic perspective" from Marsland. I find it useful as an ...
4
votes
0answers
363 views

Reversing Chebyshev inequality argument [closed]

One way one could state Chebyshev's inequality is The probability that a realization deviates from the mean more than $k$ standard deviations is at most $\frac{1}{k^2}$. My question is: Can one ...
23
votes
5answers
7k views

Alternatives to classification trees, with better predictive (e.g: CV) performance?

I am looking for an alternative to Classification Trees which might yield better predictive power. The data I am dealing with has factors for both the explanatory and the explained variables. I ...
3
votes
0answers
209 views

Proof of Theorem 7.3 in book of Probabilistic Graphical Models by Daphne Koller

I'm studying graphical models myself and reading contents about bayesian networks. When I am reading in page 371, section 8.1.4 Linear-Gaussian models, in Pattern Recognition and Machine Learning, I ...
2
votes
1answer
197 views

What's the relation among regression and classification?

I saw almost each regression method corresponds to a classification method. for example, adaboost classification, adaboost regression. What is the relationship between them? Can I get a regression ...
6
votes
0answers
2k views

Maximum entropy classifier and sentiment analysis

I am doing a project work in sentiment analysis (on Twitter data) using machine learning approach. In order to find the 'best' way to this I have experimented with naive Bayesian and maximum entropy ...
3
votes
2answers
642 views

Machine learning on big data: capability of generalization

I have being working applying different ML Algorithms oriented to Big Data and I have some open questions that I find interesting to think about. One of the first lectures about statistics begins ...
0
votes
3answers
237 views

Machine learning input relationships

After learning about a few machine-learning models (NN, SVM, decision trees), I was wondering if these models are able to find inherent relationships when learning. For example, if I feed it two ...
5
votes
3answers
2k views

Perform PCA. Extract PCs. Can one then tell what the most important _original_ features were, from the PCs? [duplicate]

Suppose that you have 1000 features, and a data set made up of say, 50,000 points. Suppose then that we perform PCA, and we extract the top 5 PCs, since they explain 99.99 percent of the variance, and ...
1
vote
1answer
65 views

Cluster “by part” instead of “as a whole”?

A definition before I start: A trajectory $t$ of length $n$ is here defined as a series of 2D coordinates $$\{(x_1,y_1), (x_2, y_2),..., (x_n, y_n)\}$$ Now I have a set comprised of such ...
0
votes
1answer
85 views

Training set as donor for test set in binary classification problem

I am wondering if there exists such a method in machine learning that: Given a binary classification problem, for each person in the test set the person that most closely resembles this person in the ...
3
votes
1answer
789 views

How to model time-series data in CRFSuite?

I recently came across the CRFSuite package for CRFs. Though, it is primarily used for NLP applications like POS tagging, i was wondering if I could use it to model time-series data as well? Have any ...
1
vote
1answer
1k views

Concerns related to neural network matlab toolbox [closed]

I have some concerns related to the use of nntool in MATLAB toolbox. Following links like this, I have found that nntool by ...
2
votes
1answer
1k views

Lower classification rate than expected by chance

I'm using scikit-learn for a small sample (36) classification problem with three features and three outputs (one output is binary and the other two are ternary). I'm using separate classifiers for ...
9
votes
6answers
5k views

Testing for stability in a time-series

Is there a standard (or best) method for testing when a given time-series has stabilized? Some motivation I have a stochastic dynamic system that outputs a value $x_t$ at each time step $t \in \...
7
votes
3answers
2k views

Machine learning techniques for time series estimation - forecasting price

Can anyone recommend any machine learning techniques for time series estimation? I have a series of times $t_{1}...t_{n}$, each having a set of associated features $f_{1}...f_{m}$, and a value $x$. ...
4
votes
1answer
321 views

Help understanding an explanation about minimum description length principle

I'm reading about MDL principle and my problem is on a book called: "Guide to intelligent data analysis", 2nd edition page 106. I have added here a picture of the page I'm having trouble with. Could ...
3
votes
1answer
3k views

Time-series machine learning methods and R packages

I am trying to determine how to use machine learning models such as for eg., random Forest with (non-financial) time-series data. Using an example, suppose we wanted to find based on monthly scores ...
1
vote
1answer
712 views

Estimating parameters in multivariate classification resulting zero determinant sample covariance matrix

Newbie here typesetting my question, so excuse me if this don't work. I am trying to give a bayesian classifier for a multivariate classification problem where input is assumed to have multivariate ...
5
votes
2answers
2k views

How to evaluate the quality of probability estimation?

I have a classifier that gives its decisions as probability estimations: for each datum it returns a set of probabilities $p_j$ for each known class $j$: $p_j(\vec{x})=P(c_{real}=j|\vec{x})$. I have ...
2
votes
2answers
3k views

Metric for probability based classification

I am doing a system for classifiying documents. The project demands the use of probability based output. So a sample will have a probability for belonging to each class. For now I use logistic ...
5
votes
1answer
2k views

Are posterior probabilities from a Naive Bayes classifier reliable?

I have read that the posterior probabilities of Naive Bayes classifiers are unreliable. Is this true? and if so, in what sense, and why? Specifically, I am interested to know if the probabilities can ...
24
votes
3answers
16k views

Cross-validation or bootstrapping to evaluate classification performance?

What is the most appropriate sampling method to evaluate the performance of a classifier on a particular data set and compare it with other classifiers? Cross-validation seems to be standard practice, ...
3
votes
1answer
2k views

Ensemble classification in MATLAB

I want to use ensemble classifiers for classification of 300 samples (15 positive samples and 285 negative samples, it means binary classification). I extracted 18 features from these samples, all of ...
1
vote
0answers
43 views

How do I get sentiment from a certain “perspective” or point-of-view?

Consider the following text The verdict is out, the jury has held MS guilty of infringements and levied penalties aggregating to $1.50Bn. It will be a massive blow to the reputation of MS. The ...
25
votes
2answers
6k views

Intuition behind logistic regression

Recently I began studying machine learning, however I failed to grasp the intuition behind logistic regression. The following are the facts about logistic regression that I understand. As the basis ...
0
votes
1answer
211 views

How to convert numerical values to ML feature in the range [0;1]?

I am supposed to extract a bunch of "generally useful" features from a piece of text. Use cases vary, but one could be text categorization. One thing that springs to mind here of course is the length ...