Machine Learning Cheat Sheet (for scikit-learn)
As you hopefully have heard, we at scikit-learn are doing a user survey (which is still open by the way). One of the requests there was to provide some sort of flow chart on how to do machine learning. As this is clearly impossible, I went to work straight away. This is the result: [edit2] clarification: With ensemble classifiers and ensemble regressors I mean random forests, extremely randomized
Scikit learnより グリッドサーãƒã«ã‚ˆã‚‹ãƒ‘ラメータ最é©åŒ–
Grid search ã¨ã¯ scikit learnã«ã¯ã‚°ãƒªãƒƒãƒ‰ã‚µãƒ¼ãƒãªã‚‹æ©Ÿèƒ½ãŒã‚る。機械å¦ç¿’モデルã®ãƒã‚¤ãƒ‘ーパラメータを自動的ã«æœ€é©åŒ–ã—ã¦ãれるã¨ã„ã†ã‚ã‚ŠãŒãŸã„機能。例ãˆã°ã€SVMãªã‚‰Cã‚„ã€kernelã‚„gammaã¨ã‹ã€‚Scikit-learnã®ãƒ¦ãƒ¼ã‚¶ãƒ¼ã‚¬ã‚¤ãƒ‰ã‚ˆã‚Šã€ä»Šå›žå‚考ã«ã—ãŸã®ã¯ã“ã¡ã‚‰ã€‚ 3.2.Parameter estimation using grid search with cross-validation Example:Parameter estimation using grid search with cross-validation ã‚„ã£ãŸã“㨠手書ãæ•°å—(0~9)ã®ãƒ‡ãƒ¼ã‚¿ã‚»ãƒƒãƒˆdigitsã‚’SVMã§åˆ†é¡ž GridSearchCVを使ã£ã¦ã€äº¤å·®æ¤œå®šã§ãƒã‚¤ãƒ‘ーパラメータを最é©åŒ– 最é©åŒ–時ã®ãƒ¢ãƒ‡ãƒ«ã®è©•ä¾¡é–¢æ•°ã«ã¯f1を使用 データã®æº–å‚™ 手書ãæ•°å—ã®digitsをインãƒ
pythonã®æ©Ÿæ¢°å¦ç¿’ライブラリscikit-learnã®ç´¹ä»‹ - 唯物是真 @Scaled_Wurm
scikit-learn(sklearn)ã®æ—¥æœ¬èªžã®å…¥é–€è¨˜äº‹ãŒã‚ã‚“ã¾ã‚Šãªã„ãªãƒ¼ã¨æ€ã£ã¦æ›¸ãã¾ã—ãŸã€‚ ã©ã¡ã‚‰ã‹ã£ã¦ã„ã†ã¨ã‚ˆã使ã†æ©Ÿèƒ½ã®ç´¹ä»‹çš„ãªæ„Ÿã˜ã§ã™ã€‚ 英語ãŒèªã‚ã‚‹æ–¹ã¯å…¬å¼ã®ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ãŒãŠã™ã™ã‚ã§ã™ã€‚ scikit-learnã¨ã¯ï¼Ÿ scikit-learnã¯ã‚ªãƒ¼ãƒ—ンソースã®æ©Ÿæ¢°å¦ç¿’ライブラリã§ã€åˆ†é¡žã‚„回帰ã€ã‚¯ãƒ©ã‚¹ã‚¿ãƒªãƒ³ã‚°ãªã©ã®æ©Ÿèƒ½ãŒå®Ÿè£…ã•ã‚Œã¦ã„ã¾ã™ã€‚ ã¾ãŸæ§˜ã€…ãªè©•ä¾¡å°ºåº¦ã‚„クãƒã‚¹ãƒãƒªãƒ‡ãƒ¼ã‚·ãƒ§ãƒ³ã€ãƒ‘ラメータã®ã‚°ãƒªãƒƒãƒ‰ã‚µãƒ¼ãƒãªã©ã®ç—’ã„ã¨ã“ã‚ã«æ‰‹ãŒå±Šã機能もã‚ã‚Šã¾ã™ã€‚ インストール scikit-learnã®ä»–ã«ã‚‚numpyã¨ã‹scipyã¨ã‹ãŒå¿…è¦ã§ã™ã€‚ Windows 64 bit版ã®äººã¯ä»¥ä¸‹ã®URLã«è‰²ã€…ãªã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ©ãƒ¼ãŒãŠã„ã¦ã‚ã‚‹ã®ã§ãŠã™ã™ã‚ Python Extension Packages for Windows - Christoph Gohlke ãã®ä»–ã®äººã¯ä»¥ä¸‹ã®URLを見ã¦
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