Fuzzy CODAS
Method object
- class pyfdm.methods.f_codas.fCODAS(normalization=<function max_normalization>, distance_1=<function euclidean_distance>, distance_2=<function hamming_distance>)[source]
Bases:
object
- __call__(matrix, weights, types, tau=0.02, *args, **kwargs)[source]
Calculates the alternatives preferences
- Parameters:
matrix (ndarray) – Decision matrix / alternatives data. Alternatives are in rows and Criteria are in columns.
weights (ndarray) – Vector of criteria weights in a crisp form
types (ndarray) – Types of criteria, 1 profit, -1 cost
tau (float, default = 0.02) – Threshold parameter
- Returns:
Preference calculated for alternatives. Greater values are placed higher in ranking
- Return type:
ndarray
Fuzzy calculations
- pyfdm.methods.codas.fuzzy.fuzzy(matrix, weights, types, normalization, distance_1, distance_2, tau)[source]
Calculates the alternatives preferences based on Triangular Fuzzy Number extension
- Parameters:
matrix (ndarray) – Decision matrix / alternatives data. Alternatives are in rows and Criteria are in columns.
weights (ndarray) – Vector of criteria weights in a crisp form
types (ndarray) – Types of criteria, 1 profit, -1 cost
normalization (callable) – Function used to normalize the decision matrix
distance_1 (callable) – Function used to calculate distance from fuzzy negative solution
distance_2 (callable) – Function used to calculate distance form fuzzy negative solution
tau (float) – Threshold parameter
- Returns:
Crisp preferences of alternatives
- Return type:
ndarray