def getSimilarityMatrix(svd_model_file): """ Returns similarity matrix from svd_model_file """ #Import SVD from file svd=SVD() svd.load_model(svd_model_file) return svd.get_matrix_similarity()
def loadSVD(): filename = 'favRate.dat' svd = SVD() svd.load_data(filename=filename, sep='::', format={'col':0, 'row':1, 'value':2}) svd.save_data("svd.dat", False) K=20 svd.compute(k=K, min_values=1, pre_normalize="rows", mean_center=False, post_normalize=True, savefile='.') #svd.recommend(USERID, n=10, only_unknowns=True, is_row=False) sparse_matrix = svd.get_matrix() sim_matrix = svd.get_matrix_similarity() print sparse_matrix #print sim_matrix #1173893,1396943 sim = svd.similar(897346, 10) filename = 'swoffering.yaml' titleStream = file(filename, 'r') titleList = yaml.load(titleStream) #print sim for row in sim: (offid, similar) = row print offid, titleList[str(offid)], similar