pymcdm
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Contents:
About
User Guide
1. MCDM methods
2. Weighting methods
3. Normalizations methods
4. Correlation module
API
Examples
pymcdm
User Guide
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User Guide
1. MCDM methods
1.1. American school
1.1.1. ARAS
1.1.2. COCOSO
1.1.3. CODAS
1.1.4. COPRAS
1.1.5. EDAS
1.1.6. ERVD
1.1.7. MABAC
1.1.8. MAIRCA
1.1.9. MARCOS
1.1.10. MOORA
1.1.11. OCRA
1.1.12. PROBID
1.1.13. RAM
1.1.14. RIM
1.1.15. SPOTIS
1.1.16. TOPSIS
1.1.17. VIKOR
1.1.18. WASPAS
1.1.19. WPM
1.1.20. WSM
1.2. European school
1.2.1. PROMETHEE II
1.3. Rule based
1.3.1. COMET
2. Weighting methods
2.1. Objective weights
2.1.1. Equal weights
2.1.2. Entropy method
2.1.3. Standard deviation method
2.1.4. MEREC
2.1.5. CRITIC method
2.1.6. CILOS method
2.1.7. IDOCRIW method
2.1.8. Angular method
2.1.9. Gini Coeficient method
2.1.10. Statistical variance method
3. Normalizations methods
3.1. Sum based
3.1.1. Sum normalization
3.1.2. Vector normalization
3.1.3. Logarithmic normalization
3.1.4. Enhanced accuracy method
3.2. Linear ratio based
3.2.1. Max normalization
3.2.2. Linear normalization
3.2.3. Nonlinear normalization
3.3. Linear max-min based
3.3.1. Min-max normalization
3.3.2. Zavadskas and Turkis normalization
4. Correlation module
4.1. Spearman correlation coefficient
4.2. Weighted Spearman correlation coefficient
4.3. Kendall rank correlation coefficient
4.4. Ranking similarity coefficient
4.5. Pearson’s correlation coefficient
4.6. Goodman-Kruskal correlation coefficient
4.7. Weighted Similarity Coefficient
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