以åå®è£ ããåç´ãã¼ã»ãããã³ã¯ç·ååé¢å¯è½ãªåé¡ãã解ããªãã£ãã ããã«å¯¾ãããµãã¼ããã¯ã¿ã¼ãã·ã³ (ä»¥ä¸ SVM) ã¯ã«ã¼ãã«é¢æ°ãç¨ãããã¨ã§ç·ååé¢ä¸å¯è½ãªåé¡ã解ããããã«ãªã£ã¦ããã ã¾ããåç´ãã¼ã»ãããã³ã§ã¯ç°ãªãã¯ã©ã¹ã¿ãåé¢ããããã®ç·ãã¯ã©ã¹ã¿ã®ã®ãªã®ãªã«é ç½®ããããã¨ãå¤ãã£ãããSVM ã§ã¯ãã®ãã¼ã¸ã³ãæ大ã«ãªãããã«ã§ãã¦ããã ä»å㯠SVM ãèªåã§æ¸ãã®ã§ã¯ãªã scikit-learn ã®ããã使ã£ãã #!/usr/bin/env python # -*- coding: utf-8 -*- import numpy as np import matplotlib.pyplot as plt from sklearn import datasets from sklearn import svm def main(): # Iris ãã¼ã¿ã»ãã
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