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main_pca.py
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main_pca.py
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from pca import *
#------------------------------- IMPORT CSV + MODIFICHE DATASET -------------------------------#
#Importiamo il csv e lo trasformiamo in una matrice
data = pd.read_csv("candy_1.csv", sep = ",", header=None)
data = data.as_matrix()
#Creiamo la matrice x
X = data[:, 0:data.shape[1]-1]
y = data[:,-1]
#----------------------------------------------------------------------------------------------#
#------------------------------------ NORMALIZAZZIONE FEATURE ---------------------------------#
#------------------------------------- ZSCORE -----------------------------------#
mu, sigma = muSigma(X)
X = zScore(X, mu, sigma)
#--------------------------------------------------------------------------------#
#------------------------------------ MINMAX ------------------------------------#
# min, diff, max = minmax(X)
# X = Min_Max(X, min, diff)
#--------------------------------------------------------------------------------#
#-------------------------------- FEATURE SCALING -------------------------------#
# min, diff, max = minmax(X)
# X = Feat_Scaling(X, max)
#--------------------------------------------------------------------------------#
#----------------------------------------------------------------------------------------------#
soglia=0.2
Z,Ureduce,S,V = best_k_PCA(X,soglia)
print("K scelto:",len(Z[0]),"\nZ: \n",Z,"\nUreduce: \n",Ureduce,"\nS: \n",S)