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Fabrice JOURDAN
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How to check/optimize cross validation with randomforest on imbalanced classes ?

Started on Thursday 0 Replies

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others…Continue

RandomForest for imbalanced classes

Started this discussion. Last reply by Fabrice JOURDAN May 14. 2 Replies

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others…Continue

 

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Fabrice JOURDAN's discussion was featured

How to check/optimize cross validation with randomforest on imbalanced classes ?

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others are booleanI use features selection in order to reduce the number of predictorsI remove predictors with lowest variance, lowest correlation with my target variable, also i use t-test (mean difference between 2 classes)I keep around 20 predictors for 150 observables in my signalNB:I didnt use yet…See More
yesterday
Fabrice JOURDAN posted a discussion

How to check/optimize cross validation with randomforest on imbalanced classes ?

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others are booleanI use features selection in order to reduce the number of predictorsI remove predictors with lowest variance, lowest correlation with my target variable, also i use t-test (mean difference between 2 classes)I keep around 20 predictors for 150 observables in my signalNB:I didnt use yet…See More
yesterday
Tim Matteson liked Fabrice JOURDAN's discussion RandomForest for imbalanced classes
Tuesday
Fabrice JOURDAN replied to Fabrice JOURDAN's discussion RandomForest for imbalanced classes
""F1-score" I determine f1-score during "Parameters tuning" of RandomForest. For each set of parameters (few hundreds) i determine the thresholdwhich give me the best f1score (mostly between 0.09 and 0.13). So i do not use display…"
May 14
Danylo Zherebetskyy replied to Fabrice JOURDAN's discussion RandomForest for imbalanced classes
"These are some questions that, hopefully, may help to move on: - for f1-score, what is the probability threshold for the classification? is it standard 0.5 or you determined it from AUROC curves? - since there is one continuous feature, the trees…"
May 14
Fabrice JOURDAN's discussion was featured

RandomForest for imbalanced classes

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others are booleanI use features selection in order to reduce the number of predictorsI remove predictors with lowest variance, lowest correlation with my target variable, also i use t-test (mean difference between 2 classes)I keep around 20 predictors for 150 observables in my signalNB:I didnt use yet…See More
May 9
Fabrice JOURDAN posted a discussion

RandomForest for imbalanced classes

Hi everybody, here's a summary of my study followed with few question on randomforestPopulation : 3300 observables, minority class 150 observables (~4%)Predictors : ~70 , just 1 numerical, all others are booleanI use features selection in order to reduce the number of predictorsI remove predictors with lowest variance, lowest correlation with my target variable, also i use t-test (mean difference between 2 classes)I keep around 20 predictors for 150 observables in my signalNB:I didnt use yet…See More
May 9

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