more detailed information in ITALIAN: REPORT.MD
Compute probability and precision of hitting missing value through different models (MLP, SVM, RandomForest, KNN).
- pandas: load and manipulation of DataSet
- numpy, collections: advanced data structures
- sklearn: algo, stats and splitting of TrainingSet
- argparse: command line script parsing
- matplotlib: graph plotting
main.py [-h] [--test-size TEST_SIZE] [--question-marks-ts QM_REPETED_TS] [--no-split]
[--img-tag IMG_TAG] [--verbose]
[DATASET]
- DATASET: [breast-cancer|letters|poker] - select DataSet. Default is breast-cancer
- --test-size TEST_SIZE, -t TEST_SIZE: [0-1] - TestSet dimension. Default 0.2
- --question-marks-ts QM_REPETED_TS, -q QM_REPETED_TS: {0,1,2...} - Number of samples added to the DataSet for all '?' in the query. Default 1
- --no-split, -s: use the whole DataSet for training. Disabled by default
- --img-tag IMG_TAG, -i IMG_TAG: string - append a string to image graph filename
- --verbose, -v: verbose mode (increase it by repeating)
- -h, --help: show help
nota: Others options could be set by source code.
The DataSet taken from archive.ics.uci.edu are: