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![]() ![]() This is why data visualizations and charts are everywhere now. I assume "probability" is the probability generated by the random forest model, and "explanation fit" measures the "explanatory power" of the LIME model.They are practical and necessary tools for conveying complex ideas and concepts without words or raw numbers. I am also not sure what is the difference between "probability" and "explanation fit". Or explainer <- lime(f, model, bin_continuous = TRUE, quantile_bins = FALSE) I am still confused whether these lines should be: explainer <- lime(f, model, bin_continuous = TRUE, quantile_bins = FALSE) Suppose I am interested in only the first observation. I don't understand what changed - but at least the graphics now show up. Plot_features(explanation, case =1:4, ncol = 1) I change the code (see below): #load libraries #visualize the results - here is the error: ![]() #run the "lime" procedure on the first observationĮxplainer <- lime(f, model, bin_continuous = TRUE, quantile_bins = FALSE)Įxplanation <- explain(f, explainer, n_labels = 1, n_features = 4) Model<-as_classifier(model, labels = NULL) ![]() Model<-randomForest(response ~., data = f, mtry=2, ntree=100) # run random forest on all the data except the first observation #declare var_3 and response_variable as factors As per the original code I was using, here is the plot: #load libraries
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