{"title":"Synthesizing Tabular Data using Generative Adversarial Networks (preprint) \u8aad\u3093\u3060","url":"https://repose.hatenadiary.jp/entry/2019/09/28/114747","image_url":"https://chart.apis.google.com/chart?cht=tx&chl=n_%7Bc%7D","author_name":"repose","width":"100%","description":"[1811.11264] Synthesizing Tabular Data using Generative Adversarial Networks] GAN \u3092\u4f7f\u3063\u3066\u8868\u5f62\u5f0f\u306e\u30c7\u30fc\u30bf\u3092\u751f\u6210\u3059\u308b\u8ad6\u6587\u306f\u65e2\u306b\u8aad\u3093\u3060\u308f\u3051\u3067\u3059\u304c\uff0c\u305d\u306e\u767a\u5c55\u5f62\uff0e \u8457\u8005\u3089\u306b\u3088\u308b\u5b9f\u88c5\u3082\u516c\u958b\u3055\u308c\u3066\u304a\u308a(DAI-Lab/TGAN: Generative adversarial training for synthesizing tabular data)\uff0c\u5b9f\u88c5\u3092\u8a66\u3057\u305f\u4eba\u3082\u3044\u308b(\u30c6\u30fc\u30d6\u30eb\u30c7\u30fc\u30bf\u5411\u3051\u306eGAN\uff08TGAN\uff09\u3067\u3001titanic\u306e\u30c7\u30fc\u30bf\u3092\u5897\u3084\u3059 - u++\u306e\u5099\u5fd8\u9332)\uff0e \u524d\u8ff0\u3057\u305f tableGAN \u3068\u306e\u9055\u3044\u306f CNN \u3092\u7528\u3044\u2026","published":"2019-09-28 11:47:47","type":"rich","blog_url":"https://repose.hatenadiary.jp/","provider_url":"https://hatena.blog","blog_title":"\u7cde\u7cde\u7cde\u30cd\u30c3\u30c8\u5f01\u6176","categories":[],"html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Frepose.hatenadiary.jp%2Fentry%2F2019%2F09%2F28%2F114747\" title=\"Synthesizing Tabular Data using Generative Adversarial Networks (preprint) \u8aad\u3093\u3060 - \u7cde\u7cde\u7cde\u30cd\u30c3\u30c8\u5f01\u6176\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","author_url":"https://blog.hatena.ne.jp/repose/","height":"190","provider_name":"Hatena Blog","version":"1.0"}