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Import the libraries
pip install numpy
pip install imblearn
pip install scipy
pip install pandas
pip install matplotlib
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Data and results stored in
/data
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Source code stored in
/src
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Other folder consists of testing code
- Linear Regression
- Naive Bayes Gaussian (same as diagonal quadratic) [theory??]
- Generalized linear model
- Decision Tree
- Extreme Learning Machine (linear kernel)
- Extreme Learning Machine (polynomial kernel)
- Extreme Learning Machine (RBF kernel)
Found in the data
directory as CSV files, PDF files and xlsx files.
- 7 sets of metrics selection techniques
- Table style For each project For Accuracy and AUC For each feature selection, make table and compare CL1 CL2 ... CL7 Without Fold1 Fold2 . . Fold5
With Fold1 Fold2 . . Fold5
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??? Make boxplot, for the AUC results. Descriptive statistics - results tabulation - write insights.
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Wilcoxon-test analysis How different are the feature selection technques?
Replace al NaN with 0. <- model does not exist.
Think of how to do the remaining 3 comparisons, you can do it!
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Classification
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Sampling
PPT Motivation Framework/Flowchart of work Tables