FAQ Database Discussion Community


what methods are there to classify documents?

machine-learning,classification,text-mining,tf-idf,feature-selection
I am trying to do document classification. But I am really confused between feature selections and tf-idf. Are they the same or two different ways of doing classification? Hope somebody can tell me? I am not really sure that my question will make sense to you guys....

Classifier extraction from MLSeq R package

r,random-forest,feature-selection
I'm currently reasonably new to R and am having trouble extracting the information I would like from a package. I am using MLSeq to implement Random Forest on RNA Seq data to find biomarkers for a condition. Currently, the output given by default is just how well it classified the...

In sklearn, does a fitted pipeline reapply every transform?

python,scikit-learn,pipeline,feature-selection
Apologies if this is obvious but I couldn't find a clear answer to this: Say I've used a pretty typical pipeline: feat_sel = RandomizedLogisticRegression() clf = RandomForestClassifier() pl = Pipeline([ ('preprocessing', preprocessing.StandardScaler()), ('feature_selection', feat_sel), ('classification', clf)]) pl.fit(X,y) Now when I apply pl on a new set, pl.predict(X_classify); is RandomizedLogisticRegression going...

python: How to get real feature name from feature_importances

python,scikit-learn,classification,feature-selection
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: venue_feature_start.append(Counter(trip['POI'])) # Counter(trip['POI']) is like Counter({'school':1, 'hospital':1, 'bus station':2}),actually key is the feature feat_loc_vectorizer = DictVectorizer() feat_loc_vectorizer.fit(venue_feature_start) feat_loc_orig_mat = feat_loc_vectorizer.transform(venue_feature_start)...

How to select features for random forest using varImp function?

r,random-forest,feature-selection
I have applied random forest on a training data which has about 100 features. Now I would like to apply feature selection technique in order to reduce the number of features before applying random forest model on the data. How can I make use of varImp function (from caret package)...

scikit-learn pipeline

python,scikit-learn,pipeline,feature-selection
Each sample in My (iid) dataset looks like this: x = [a_1,a_2...a_N,b_1,b_2...b_M] I also have the label of each sample (This is supervised learning) The a features are very sparse (namely bag-of-words representation), while the b features are dense (integers,there are ~45 of those) I am using scikit-learn, and...

Merging features to one just gives back a feature with braking lines within

merge,polygon,qgis,feature-selection
I have a similar question to this one: "snapping" polygons together I have drawn let's say 3 areas. The 1. is overlapping with the 2. and the 2. is overlapping with the 3. I made sure that I was using the snapping tool and the outer lines are matching each...

How to combine two (or multiple) kinds of features as one final feature to build classification model?

machine-learning,classification,feature-extraction,feature-selection
Currently, I meeting such question:How to combine two (or multiple) kinds of features as one final feature to build classification model? For example, I would like to do a classification model to predict the drug-target interaction, here for each drug I can get 500 features, and each targets I can...

R language: Can the function rfe of the package caret be used with a mixed effect model

r,feature-selection,caret,nlme
I would like to do feature selection with a mixed effect model in R, but I cannot manage to combine the function rfe of the package caret with the function me of the package nlme. Here is a example that works but does not use a mixed effect model: data(iris)...

Feature extraction from multiple curves

machine-learning,svm,feature-extraction,feature-selection
I got multiple curves from different sensor but all attached in the same moving object. Now I want to extract features from it , let's say I have cut 0-10 as window1 , so in window1 I got 5 graphs ,each graph represents one sensor in a particular position, each...

Multiple Scope value in Binding (Specflow)

scope,automated-tests,specflow,feature-selection,feature-file
I have a method which runs Before a feature like so, [BeforeFeature, Scope(Feature = "Feature1"] Method() { } I want the same method to be ran for another feature file that i've wiritten i.e. Feature2 How do i combine this "Feature2" in the scope Binding? I tried this [BeforeFeature, Scope(Feature...