Methods and principles of selecting a subset of attributes for use in further modelling

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Feature Selection

I've a facebook users dataset in which each user has a "huge" set of attribute, i.e about 220 attributes like age, hometown, religion, and a set of facebook liked pages to store the users tastes. Now ...
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8 views

Redundant feature generation

I'm evaluating a few supervised feature selection algorithms, with a focus on redundancy. As a base correlation statistic, I'm using Mutual Information - so discrete variables are also a focus for ...
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What kinds of features are worth taking from objects on images?

I managed to label and get set of pixels for every single object of interest in the image. Now I'm looking into clustering and am not sure what features are worth using. I currently have two in mind ...
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44 views

Feature selection for one class SVM

I have around 300 features, i need to choose features for one class svm. can some one tell me the ideal algorithm for this use case. I know about that for feature selection regularised random ...
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1answer
109 views

Does Boruta feature selection (in R) take into account the correlation between variables?

I am a bit of a novice in R and feature selection, and have tried the Boruta package to select (diminish) my number of variables (n= 40). I thought that this method also took into account the possible ...
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10 views

How to train input feature weights for a path optimization problem?

I am working on a general path optimization problem. As many of you know, once the weights on all nodes are determined, one may solve this problem in many different means. Unfortunately, my raw input ...
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26 views

Using selected features from a wrapper algorithm to train another model

I was wondering if it can be useful to use selected features from a wrapper algorithm (for example SVM-RFE) to train another classification model like k-NN or Linear regression.
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56 views

Feature selection with SNP datasets

I'm working with a Single-nucleotide polymorphism (SNP) dataset with over 2.2 million features and roughly 2000 samples. I wish to do feature selection on this dataset to reduce it down to ...
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23 views

Is mRMR feature selection sensitive to imbalanced dataset?

I wish to perform feature selection on a dataset using mRMR but my classes are imbalanced roughly 3:1. Should I down sample the majority class or use the whole dataset? If I use the whole dataset will ...
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25 views

Updating set of probabilities for sampling with features importance

I'm currently working on some algorithm and I'm kinda out of idea for a problem I'm trying to tacle. Basically I'm trying to subsample the features of a dataset. I want to subsample that given this ...
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188 views

How to select a model in quasi-poisson GLM with interactions using drop1 command?

I want to evaluate the effect of three factors (one categorical, and the other two continuous) on the response variable, which is a count data. I have performed 7 candidate GLM models with ...
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32 views

Nonlinear problem feature selection

I am trying to make prediction of students course score with neural networks. I have lots of parameters may affect to one course score like sex, GPA and many previous course scores. Before trying to ...
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458 views

HOG Feature Implementation with SVM in MATLAB

I would like to do classification based on HOG Features using SVM. I understand that HOG features is the combination of all the histograms in every cell (i.e. it becomes one aggregate histogram). ...
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1answer
95 views

Identify original features corresponding to high singular/principal component values [duplicate]

In MATLAB, while SVD gives a diagonal matrix S of decreasing singular values, PCA gives a column vector LATENT of decreasing principal component values. How can S be used to obtain a subset of ...
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293 views

HIstogram of oriented gradients (HOG) features descriptor theoretical problems

I'm going to implement HOG as my features descriptor. But there are some things that make me confused: For example: If we have an image with size of 10 x 20 If we want to compute the HOG of that ...
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147 views

Finding interactions using randomForest

I am trying to use randomForest in R to find interaction terms to add to a model. My plan was to fit trees with maxnodes=4 (two ...
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1answer
184 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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51 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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44 views

What are some classic examples of feature selection in classification?

Is there a classic example showing the importance of good feature selection in classification? The ideal example would be simple, and very easy to understand. I've been volunteered/instructed to put ...
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1k views

The main effect will be non-significant if the interaction is significant? [duplicate]

I am using linear mixed models to identify important factors, and it turns out that: A: significant B: not significant ...
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1answer
89 views

What is parameter fine tuning means in SVM?

I got this sentence in one of paper, but I dont understand what does it mean?? "Training a learningbased classifier such as an SVM on an imbalanced dataset often requires parameter fine-tuning, ...
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38 views

How to determine the factors correlated with observed data?

I have box-office collection data on a number of movies. I also have the production budget, director name, lead actor, actress, language and other meta data related to the movie. I want to know which ...
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1answer
80 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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1k views

Can independent variables with low correlation with dependent variable be significant predictors?

I have eight independent variables and one dependent. I have run a correlation matrix, and 5 of them have a low correlation with the DV. I have then run a stepwise multiple regression to see whether ...
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115 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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20 views

Variable Selection Methods in R [duplicate]

regsubsets and stepAIC are the two most common options for variable selection in R; they can be found in the ...
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28 views

Detecting noisy patterns in document images

I am looking for features to extract to distinguish between text objects and arbitrary noisy patterns in degraded document images. This is an example of a document with some parts of noise, I have ...
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12 views

Error trying to reduce my data dimentions [duplicate]

I'm trying to produce a linear regression model, but I only have 25 observations and 34 predictors. I'm trying feature selection, ...
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1answer
187 views

How to use rfe object with function pickSizeTolerance in R package caret

I run caret's recursive feature selection with randomForest. While running rfe function with method repeatedcv, I had parameter ...
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19 views

How to extract “average polyline” from a set of polylines [duplicate]

EDIT: As pointed, there is already a similar question "buried" inside a larger-scope one. I'll reproduce the relevant part here: If I have multiple recordings of the same routes are there any ...
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1answer
75 views

Feature selection for pattern mining

I must find frequent patterns in temporal data, using a method that was imposed to me. This tool has problems handling these data: processing is long and takes a lot of memory. So, I would like to ...
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20 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 ...
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1answer
176 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 ...
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58 views

Why do Laplacian Eigenmaps ignore the second KKT condition in the solution calculation?

From the original Laplacian Eigenmaps paper, we find the new manifold embedding $Y$ as follows, given the Laplacian and degree matrices $L$ and $D$: $\arg\min_Ytr(Y^TLY)$ subject to ${Y^TDY=I}$. ...
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29 views

Clustering and Feature Selection For Audio Data

I'm very new to stats and I'm at a loss as to where to start with this problem. I'm not sure what tools or methods to use to extract meaningful answers from my data. I'll try and describe the problem ...
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55 views

Selecting features and estimating their out-of-sample performance with cross-validation

I have only a small dataset. I want to 1. select the most predictive features out of a large candidate pool and 2. get an estimate of their expected predictive performance. In the elements of ...
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Quantify the information lost given by the Kullback-Leibler divergence measure

Consider there are $N$ individuals and these measure a quantity $X\in \mathbb{R}^{N\times M}$ where $M$ is the number of measurements and let $P(X)$ denote a probability distribution over $X$. The ...
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1answer
36 views

Term selection in a model

In selecting terms to include in a model, say a linear one, should we always test the significance of the main effects first, keep only the significant ones, then consider the possible interactions ...
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69 views

Recursive feature extraction with random forests following by statistical inference?

I have a small dataset of n = 200 with about 80 predictors. The outcome I am working with is binary. I'm interested in doing a two-step process where: (1) I conducted recursive feature extraction ...
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476 views

Cross-validation and feature selection of a multivariate regression

I've been trying to create a multivariate regression model to fit my training data into the prediction of a value. I've put my data into a matrix X with ...
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58 views

Linear regression for feature selection

Imagine we regress y on x1...x4. Now, we want to find out if ...
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82 views

Advice for interpolating a model

I'm new in Stack Exchange, so I hope no to be off topic. I'm also new in bioinformatics and I was asked to perform an analysis. Briefly, I have a dataset of 29 cell lines and the IC50 values of a test ...
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1answer
190 views

Interpreting the lasso coefficients

I have used lasso logistic regression on some data and I have some non zero coefficients for some of the features. I want to know based upon the coefficient values how do I rank the features?
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50 views

Feature selection for support vector regression with time series as features

I would like to select features for a support vector regression for forecasting. I would like to forecast a value at point t with the values t-1,...t-x as features. Now I want to select the most ...
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1answer
46 views

How to compare features and classifiers which achieve perfect accuracy?

So I'm looking to compare different combinations of features and classifiers. But I'm getting a lot of combinations that achieve 100% cross validation accuracy. I'm trying to figure out how I would ...
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61 views

How to compare features and classifiers which achieve perfect accuracy?

So I'm looking to compare different combinations of features and classifiers. But I'm getting a lot of combinations that achieve 100% cross validation accuracy. I'm trying to figure out how I would ...
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1answer
48 views

Feature selection while retaining a specified feature

Pardon if this question is very basic, but I am not able to find any solution for my problem. I am trying to run a feature selection scheme on N features for my classification model, however I want ...
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36 views

Proper way to determine attribute feature selection's smaller subset based on result metrics

Overview My goal is to predict survival of an instance for five different time periods (binary attribute). I have a 100,000-instance dataset with 40 attributes and I want to reduce the attributes ...
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169 views

Variable selection for regression - the subselect package

No regular here will be unaware of the perils of using stepwise and similar automatic methods for variable selection in regression analysis. But preferred alternatives, such as the lasso or ...