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Questions tagged [feature-selection]

In machine learning, this is the process of selecting a subset of most relevant features to construction your data model.

Feature selection is an important step to remove irrelevant or redundant features from our data. For more details, see Wikipedia.

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How to get attribute list from fitted model in Scikit-learn?

Is there any way to get a list of features (attributes) from used model in Scikit-learn (or whole table of used training data)? I am using some preprocessing like feature selection and I would like to know features that were selected and features…
Bohemiak
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How to apply filter based feature selection for logistic regression in R's caret package?

I am trying to apply filter based feature selection in caret package for logistic regression. I was successful at using sbf() function for random forest and LDA models (using rfSBF and ldaSBF respectively). The way I modified lmSBF is as follows: #…
exAres
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python: How to get real feature name from feature_importances

I am using Python's sklearn random forest (ensemble.RandomForestClassifier) to do classification and am using feature_importances_ to find significant feature for the classifier. Now my code is: for trip in database: …
gladys0313
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feature selection in wrapper method and information filtering?

I see one example in old-mid exam from well-known person Tom Mitchell, as follows: Consider learning a classifier in a situation with 1000 features total. 50 of them are truly informative about class. Another 50 features are direct copies of the…
user4591951
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Vowpal Wabbit ignore linear terms, only keep interaction terms

Hi have a Vowpal Wabbit file with two namespaces, for example: 1.0 |A snow |B ski:10 0.0 |A snow |B walk:10 1.0 |A clear |B walk:10 0.0 |A clear |B walk:5 1.0 |A clear |B walk:100 1.0 |A clear |B walk:15 Using -q AB, I can get the interaction…
Manor Lev Tov
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How can sklearn select categorical features based on feature selection

My question is i want to run feature selection on the data with several categorical variables. I have used get_dummies in pandas to generate all the sparse matrix for these categorical variables. My question is how sklearn knows that one specific…
MYjx
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Visual Studio 2013 Optional Features to Install

I am installing visual studio 2013 professional edition on my development box and have question on what features need to install .. I am going to develop a MVC or Web Forms Web Application which communicates to SQL Server 2005 I want to install…
msbyuva
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How to rank features by their importance in a Weka classifier?

I use Weka to successfully build a classifier. I would now like to evaluate how effective or important my features are. Fot this I use AttributeSelection. But I don't know how to ouput the different features with their corresponding importance. I…
khadre
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Using Bhattacharyya Distance for feature selection

I have a set of 240 features extracted using Image Processing. The objective is to classify test cases into 7 different classes after training. For each class there are about 60 observations(viz, I have around 60 feature vectors for each class with…
Sohaib
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glmulti Oversized candidate set

Error message: SYSTEM: win7/64bit/ultimate/16gb-real-ram plus virtual memory, memory.limit(32000) What does this error message mean? In glmulti(y = "y", data = mydf, xr = c("x1", : !Oversized candidate set. mydf has 3.6mm rows & 150…
Yu Le
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Feature Importance with SVR

I would like to plot Feature Importance with SVR, but I don't know if possible with support vector regression it's my code. from sklearn.svm import SVR C=1e3 svr_lin = SVR(kernel="linear", C=C) y_lin = svr_lin.fit(X,Y).predict(X) scores =…
Juan Carlos
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What we should do with highly correlated features?

In my data set 2 features C1 and C2 are highly correlated. I did following steps. Could you please let me know if it is correct and make sense? do you have a better approach? First I used linear model to find the fitted line: C1=a*C2+b from sklearn…
user12904074
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Pandas dataframe divide features to group of high correlation

I have a dataframe with over 280 features. I ran correlation map to detect groups of features that are highly correlated: Now, I want to divide the features to groups, such that each group will be a "red zone", meaning each group will have features…
Cranjis
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How to select best features in Dataframe using the Information Gain measure in scikit-learn

I want to identify the 10 best features of a Dataframe using the Information Gain measure (Mutual Info in scikit-learn) and display them in a table (in ascending order according to the score obtained by the Information Gain). In this example,…
Lynn
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Correlation coefficient explanation--Feature Selection

How to determine the variables to be removed from our model based on the Correlation coefficient . See below Example of variables: Top 10 Absolute Correlations: Variable 1 Variable 2 Correlation Value pdays pmonths …
Hell Boy
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