"Figure 9a: When classification performance is high (as for dresses), indices are tight and co-move closely, whereas decision trees are poor-performing classifiers and diverge","" "","" "","" "Notes","" "Unit","" "","" "Month","Decision Tree","Logistic Regression","Random Forest","Support Vector Machine","XGBoost" "Jan-19","1","1","1","1","1" "Feb-19","0.9704668","0.9721215","0.966143","0.9700858","0.96432614" "Mar-19","0.9430855","0.9375628","0.9304596","0.9327448","0.93008816" "Apr-19","0.9317222","0.9281674","0.91803116","0.92411554","0.91917884" "May-19","0.93773913","0.9334404","0.9256284","0.9269344","0.92400414" "Jun-19","0.8974581","0.88359255","0.8781255","0.87743115","0.8744434" "Jul-19","0.8536971","0.836003","0.8243133","0.8277419","0.8283429" "Aug-19","0.8555603","0.8230762","0.8080713","0.812611","0.80693513" "Sep-19","0.8671104","0.82552636","0.8106227","0.8163417","0.8122547" "Oct-19","0.87700975","0.81905484","0.8160988","0.8092568","0.8153028" "Nov-19","0.8679178","0.8145197","0.80050695","0.80798465","0.80585253" "Dec-19","0.86563057","0.8091908","0.7954842","0.8036739","0.80501753" "Jan-20","0.854248","0.80498886","0.7714769","0.8007782","0.7726874"