In machine learning, this is the process of selecting a subset of most relevant features to construction your data model.
I use Weka to successfully build a classifier. I would now like to evaluate how effective or important my features …
machine-learning nlp weka feature-selection text-classificationWhen I plot the feature importance, I get this messy plot. I have more than 7000 variables. I understand the built-in …
python matplotlib machine-learning xgboost feature-selectionI have fit a logistic regression model to my data. Imagine, I have four features: 1) which condition the participant received, 2) …
python scikit-learn logistic-regression feature-selection coefficientsi used pipeline and grid_search to select the best parameters and then used these parameters to fit the best …
scikit-learn pipeline feature-selectionDoes anybody how the numbers are calculated? In the documentation it says that this function "Get feature importance of each …
python feature-selection xgboostI am using Python's sklearn random forest (ensemble.RandomForestClassifier) to do classification and am using feature_importances_ to find significant …
python scikit-learn classification feature-selectionI running kmeans in matlab on a 400x1000 matrix and for some reason whenever I run the algorithm I get …
matlab k-means feature-selectionI was trying to find the best features that dominate for the output of my regression model, Following is my …
python-3.x scikit-learn deep-learning keras feature-selectionI'm experimenting with Chi-2 feature selection for some text classification tasks. I understand that Chi-2 test checks the dependencies B/…
machine-learning scikit-learn feature-selectionI am installing visual studio 2013 professional edition on my development box and have question on what features need to install .. …
installation visual-studio-2013 feature-selection