Category : mlxtend

I want to do a FeatureSelection with the mlxtend ExhaustiveFeatureSelector. My current Pipeline is simply: regr = make_pipeline(StandardScaler(), SVR()) I have also categorical attributes, which i have manually encoded with the OneHotEncoder() before setting up the pipeline. df = onehot(df,"Categorical_Attribute") X = df.drop(‘Target_Variable’, axis=1) y = df[‘Target_Variable’] Now i want start the Feature Selection but ..

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I’m trying to plot a binary decision boundary using the mlxtend library (http://rasbt.github.io/mlxtend/), but I’m encountering the following error: UserWarning: No contour levels were found within the data range. ax.contour(xx, yy, Z, cset.levels, This is the code I’m using to produce the plot: import itertools from mlxtend.plotting import plot_decision_regions from sklearn.decomposition import PCA pca = ..

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If I use the following code snippet: for i in (apriori(data_frame, min_support=0.001, use_colnames=True)): print(i) I get the result: support itemsets However if I use print(apriori(data_frame, min_support=0.001, use_colnames=True)) I get the full result, i.e. all the elements under the columns "support" and "itemset". I want to be able to access all of these elements individually as ..

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