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Questions tagged [rfe]

Recursive Feature Elimination. This algorithm implements backwards selection of predictors based on predictor importance ranking. The predictors are ranked and the less important ones are sequentially eliminated prior to modelling. The goal is to find a subset of predictors that can be used to produce an accurate model.

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Sklearn Predict_Proba: ValueError: operands could not be broadcast together with shapes (44,57) (4,)

I am trying to computer the log_loss of a machine learning model through recursive feature elimination and a value error occurs when I try to run sklearns predict_proba function I have currently tried to remove the code that refits my dataset…
biazing
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Multi-output regressor and sklearn's RFE module

I was wondering if it is possible to do RFE using a multi-variate estimator with sklearn package. I checked the documentation and I can't find anything for or against it. Here is the minimal code: import sklearn.linear_model as skl from…
Blade
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How to interpret importance of features from _coeffs outputs for multi-class in sklearn.feature_selection?

I have a dataset of 150 samples and almost 10000 features. I have clustered the samples in 6 clusters. I have used sklearn.feature_selection.RFECV method to reduce the number of features. The method estimate the number of important features 3000…
arta
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Code to run recursive feature extraction multiple iteration each time deleating the lowest ranked feature

Ok so I want to run recursive feature extraction on my dataset with X amount of features and at each iteration remove the lowest ranked feature than re-run the RFE until I am only left with 5 features. However, I have no idea how to code this. The…
user3111739
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Data preparation before RFECV or any other feature selection

I'm trying to figure out if it is wise to remove highly correlated and negatively correlated features before feature selection. Here's a snapshot of my code def find_correlation(data, threshold=0.9, remove_negative=False): corr_mat =…
Joanna Teh
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Stacking StandardScaler() with RFECV and GridSearchCV

So I found out that StandardScaler() can make my RFECV inside my GridSearchCV with each on a nested 3-fold cross validation run faster. Without StandardScaler(), my code was running for more than 2 days, so I canceled and decided to inject…
chmscrbbrfck
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Implementing SVM RFE and cannot locate library

I'm looking to set up SVM RFE and found the SO article here: Implementation of SVM-RFE Algorithm in R It appears that the SVM function in the code is different from that in the e1071 library and i've been looking around to find the library with the…
Ehren
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Recursive feature elemination with CV doesn't reduce feature count

I have this protein dataset that I need to perform a RFE on. There are 100 examples with binary class labels (sick - 1, healthy - 0) and 9847 features for each example. To reduce the dimensionality I am performing a RFECV with a LogisticRegression…
the_man_in_black
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Error in { : task 1 failed - "argument is of length zero" in rfe-svm using ROC

library(LiblineaR) library(kernlab) library(caret) packageVersion('caret') library(doMC) registerDoMC(cores=4) # load dataset iris <- iris[1:100,] iris$Species <- as.factor(as.character(iris$Species)) # set…
wusixer
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Citation to Recursive Feature Elimination with CV Algorithm

Does anyone know the citation to the article from where RFECV is based upon? I have looked into the documentation and here and found nothing about it. Looking here I found the following reference http://rdcu.be/xFbx but there is no explicit…
Dino
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ggplot: How to change the visualisation of an RFE plot?

I have an RFE output,rfe2014, saved from another R session: Variables Accuracy Kappa AccuracySD KappaSD Selected 15 0.7534 0.7107 0.04265 0.04996 25 0.7808 0.7429 0.03510 0.04120 35 0.7905 0.7542 0.03460…
wowbag
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R caret package rfe error - "argument is not interpretable as logical"

I am trying to use rfeControl and rfe for a simple feature selection task using svm. The input file is small and has 20 features with 414 samples. The input can be found here…
tacqy2
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RFE giving same accuracy for different number of features selected

In the program, I am scanning a number of brain samples taken in a time series of 40 x 64 x 64 images every 2.5 seconds. The number of 'voxels' (3D pixels) in each image is thus ~ 168,000 ish (40 * 64 * 64), each of which is a 'feature' for an image…
Ajay H
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Stepping into RFE and getting 'DataFrame object is not callable" error

I'm trying to use RFE for the first time and banging my head against a "DataFrame object is not callable" error. Here is my code X, y = df5(n_samples=875, n_features=10, random_state=0) estimator = SVR(kernel="linear") selector =…
ajbentley
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Scikit learn for ranking features using RFE including scores

I would like to find the importance of each feature in my dataframe using Scikit learn. I am trying to use it in Scikit learn instead of using Info Gain via WEKA software which provide the score and the feature name next to it. I implemented the…
Aviade
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