èªç¶è¨èªå¦çã®ææ³ã®ï¼ã¤ã«ãæ½å¨çæå³è§£æ(LSA)ã¨ãããã®ãããã åèªææ¸è¡åAããã£ãå ´åãç¹ç°å¤å解(SVD)ã«ãã A=UΣV ã«å解ããç¹ç°å¤ã大ããã»ãããkå使ã£ã¦ Ak=ï¼µkΣkVk ã®ããã«éæ°ã®ä½æ¸ãè¡ããã¨ã§ãéæ°kã®ï¼¡ã¸ã®è¿ä¼¼ãæå°èª¤å·®ã§å¾ããã¨ãã§ããã ã¤ã¾ãç¹ç°å¤å解ã®è¨ç®ããã§ãã¦ãã¾ãã°LSAãããã§ããããã ãã pythonã®æ°å¤è§£æã¢ã¸ã¥ã¼ã«Scipyã«ãããã°ç¹ç°å¤å解ããã£ã¨ããéã§ããã ã¾ãã¯ç¹ç°å¤å解ã¾ã§â from numpy import * from scipy import linalg A = matrix([ [5, 8, 9, -4, 2, 4], [2, -4, 9, 4, 3, 3], [-3, 4, 8, 0, 5, 6], [-2, 5, 4, 7, 0, 2] ]) u, sigma, v = linalg.sv
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