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

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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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1answer
173 views

Choosing one variable from each of 3 buckets of variables

I have a regression model that looks like the following glm.nb(formula = y ~ Gender + Age + x1 + x2 + x3, data = df) In my problem, there are 20 possible choices ...
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3 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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2answers
53 views

Choosing the best featureset for prediction

I have this N sets of features F each with $F_i$ number of features. All the feature sets have 20000 examples and we have 20,000 labels for them. Lets say feature set $F_1$ has 10 features and ...
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2answers
29 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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1answer
136 views

Determining conserved features using a Bayesian approach

I would like to perform some sort of binary classification, and my data set consists of 100 examples (for each class), which are vectors with 2500 elements. Ideally, I would like to determine which ...
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1answer
198 views

What is a good Gini decrease cutoff for feature inclusion based upon random forests?

I am using random forests to try and determine variable importance as part of feature selection for a model I'm working on, and while I can get ranked variable importance by mean decrease in Gini from ...
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1answer
20 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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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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1answer
163 views

How to perform step() when n < p in R?

I am trying to perform stepwise regression for variable selection in R. In matlab, the stepwisefit function is able to work in ...
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1answer
19 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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1answer
42 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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2answers
49 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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16 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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1answer
71 views

How to find important features in this problem

I was just thinking how ML techniques can be applied in the retail industry. Suppose we have data from a retailer who deals with apparel and cloth in this format and for each item there are ...
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1answer
47 views

Extract important features

Here is my situation: - A huge amount of data - 600 features - Only one class is provided Now, my question is how can I reduce the number of features to important ones? In another word, all of these ...
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3answers
207 views

Feature selection before SVM

I have a simple but difficult question. Does feature selection before SVM help? I have a data set that has ~1100 features but a lot of these are redundant data / uncorrelated data. Can someone give me ...
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17 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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35 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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32 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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3answers
142 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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4answers
4k views

Using LASSO from lars (or glmnet) package in R for variable selection

Sorry if this question comes across a little basic. I am looking to use LASSO variable selection for a multiple linear regression model in R. I have 15 predictors, one of which is categorical(will ...
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1answer
106 views

Evaluating features and similarity measures

I am currently developing a classificator, which is supposed to classify into a number of classes. For this purpose I am designing some features and similarity measures which I might use for a later ...
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3answers
213 views

How to divide feature set for selection and training

I have training data with 260 observations that have a total of 7 classes. Each observation has 120 features. I applied feature selection based on the Bhattacharyya Algorithm and got the top 40 ...
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2answers
705 views

Issues with feature selection in matlab

I am trying to use sequentialfs to do some feature selection in matlab. I have huge dimensional data of 22215 features. When I tried to use sequentialfs with svm as classifier so that it selects the ...
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1answer
47 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
29 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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1answer
29 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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1answer
24 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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24 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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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
144 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
148 views

Feature selection in the training set

I have a classifier, and I am using leave one out cross-validation to assess its performance. On each iteration, I divide the dataset into training and testing sets. The testing set is just the ...
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0answers
29 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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1answer
54 views

Numeric example of data for special case of stepwise linear regression

Stepwise Regression works as follows if I'm correct: fit the initial model add the variable which has its f-stat larger than a in-threshold and repeat step 2. if there are no candidates to enter - ...
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2answers
252 views

Clustering time series with wavelets in R

Can discrete wavelet trasform be used for feature extraction from time series in order to cluster them? Any R code how to do this will be appreciated.
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1answer
26 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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2answers
23 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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3answers
21 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
62 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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11 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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1answer
44 views

finding an optimal subgroup of binary indicators

My dependent variable is continuous variable that measures the (potential) success of a person in some activity. I have hundreds of binary indicators, each indicates about the existence of a specific ...
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2answers
84 views

improve precision in text classification

I am working on binary text classification using sklearn: The length of each sample is not high (~ 200-500 characters) I use TF-IDF to get important words as TfidfVectorizer(sublinear_tf=False, ...
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18 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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1answer
79 views

Explain steps of LLE (local linear embedding) algorithm?

I understand the basic principle behind the algorithm for LLE consists of three steps. Finding the neighborhood of each data point by some metric such as k-nn. Find weights for each neighbor which ...
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0answers
11 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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0answers
18 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
43 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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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 ...