{"id":4904,"date":"2020-06-08T23:32:19","date_gmt":"2020-06-08T14:32:19","guid":{"rendered":"https:\/\/transynk.co.jp\/?post_type=blog&#038;p=4904"},"modified":"2024-07-03T23:47:32","modified_gmt":"2024-07-03T14:47:32","slug":"overfitting","status":"publish","type":"blog","link":"https:\/\/transynk.co.jp\/en\/blog\/overfitting\/","title":{"rendered":"\u6a5f\u68b0\u5b66\u7fd2\u306b\u304a\u3051\u308b\u300c\u904e\u5b66\u7fd2\u300d\u306e\u539f\u56e0\u3068\u56de\u907f\u6cd5\u3092\u89e3\u8aac"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" 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href=\"https:\/\/www.techcrowd.jp\/machinelearning\/regularization\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u3053\u3061\u3089\u306e\u8a18\u4e8b\u3082\u3054\u53c2\u7167\u304f\u3060\u3055\u3044\u3002<\/a><\/p>\n<p>\u6559\u5e2b\u30c7\u30fc\u30bf\u306e\u91cf\u304c\u4e0d\u5341\u5206\u3067\u3082\u904e\u5b66\u7fd2\u306f\u8d77\u304d\u307e\u3059\u3002\u753b\u50cf\u3092\u6271\u3063\u3066\u3044\u308b\u5834\u5408\u3001<a href=\"\/blog\/data-augmentation-image-datasets\/\">\u30c7\u30fc\u30bf\u62e1\u5f35<\/a>\u3067\u6bd4\u8f03\u7684\u7c21\u5358\u306b\u30c7\u30fc\u30bf\u306e\u4e0d\u8db3\u3092\u88dc\u3046\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u5927\u898f\u6a21\u306a\u6a5f\u68b0\u5b66\u7fd2\u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u306e\u6559\u5e2b\u30c7\u30fc\u30bf\u3067\u304a\u56f0\u308a\u306e\u65b9\u306f\u3001\u5f53\u793e\u306e\u6559\u5e2b\u30c7\u30fc\u30bf\u4f5c\u6210\/\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3\u30b5\u30fc\u30d3\u30b9\u306b\u3064\u3044\u3066\u304a\u6c17\u8efd\u306b<a 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