Pipeline feedback?

I built several models with a lot of trial and error on an imbalanced dataset (93% - 7%) and in the end selected the best performing according to the condition "More than 50% TN, max possible TP".

Model configuration:

* Algorithm: SVM
* Missing values thr.: 70%
* variance thr.: 0.05
* correlation thr.: 80%
* outlier action: substitute-4s
* scaling method: standard
* imputation method: knn
* feature selection: none
* imbalance: undersampling

The model ended up with 150 …

algorithm correlation datascience dataset error feedback max missing values outlier pipeline svm values variance