Python code (jupyter) for Machine learning
Budget: $250 – $750 USD
I want a script for my project. I have a dataset containing 8115 features split into (train and test) and I want to apply a double or hybrid filter feature selection method (FS1+FS2).
1-apply FS1 to get a subset of features.
2-apply FS2 to get another subset of features.
3-from subset 1 and subset 2, you need to suggest a mathematical equation to select the best feature selection from (subset 1 and subset 2) without duplication of features.
4-The features extracted from this equation apply its effectiveness to machine learning classification algorithms (KNN, SVM, NB, LR, DT, RF, ANN).
1-apply FS1 to get a subset of features.
2-apply FS2 to get another subset of features.
3-from subset 1 and subset 2, you need to suggest a mathematical equation to select the best feature selection from (subset 1 and subset 2) without duplication of features.
4-The features extracted from this equation apply its effectiveness to machine learning classification algorithms (KNN, SVM, NB, LR, DT, RF, ANN).