{"id":462,"date":"2020-04-04T20:48:06","date_gmt":"2020-04-04T11:48:06","guid":{"rendered":"https:\/\/www.skyer9.pe.kr\/wordpress\/?p=462"},"modified":"2020-04-04T20:48:06","modified_gmt":"2020-04-04T11:48:06","slug":"keras-%eb%a5%bc-%ec%9d%b4%ec%9a%a9%ed%95%9c-%eb%8b%a4%ec%a4%91-%ec%84%a0%ed%98%95-%ed%9a%8c%ea%b7%80","status":"publish","type":"post","link":"https:\/\/www.skyer9.pe.kr\/wordpress\/?p=462","title":{"rendered":"keras \ub97c \uc774\uc6a9\ud55c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0"},"content":{"rendered":"<h1>keras \ub97c \uc774\uc6a9\ud55c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0<\/h1>\n<pre><code class=\"language-python\">from keras.models import Sequential\nfrom keras.layers import Dense\nfrom sklearn.model_selection import train_test_split\nimport pandas as pd\n\ndf = pd.read_csv(&quot;\/home\/ubuntu\/workspace\/datasets\/streeteasy\/manhattan.csv&quot;)\n# df.head()\n\nX = df[[&#039;bedrooms&#039;,\n        &#039;bathrooms&#039;,\n        &#039;size_sqft&#039;,\n        &#039;min_to_subway&#039;,\n        &#039;floor&#039;,\n        &#039;building_age_yrs&#039;,\n        &#039;no_fee&#039;,\n        &#039;has_roofdeck&#039;,\n        &#039;has_washer_dryer&#039;,\n        &#039;has_doorman&#039;,\n        &#039;has_elevator&#039;,\n        &#039;has_dishwasher&#039;,\n        &#039;has_patio&#039;,\n        &#039;has_gym&#039;]]\ny = df[[&#039;rent&#039;]]\n\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)\n\nmodel = Sequential()\nmodel.add(Dense(30, input_dim=14, activation=&#039;relu&#039;))\nmodel.add(Dense(6, activation=&#039;relu&#039;))\nmodel.add(Dense(1))\n\nmodel.compile(loss=&#039;mean_squared_error&#039;, optimizer=&#039;adam&#039;)\n\nmodel.fit(X_train, y_train, epochs=200, batch_size=10)\n\nscore = model.evaluate(X_test, y_test, batch_size=10)\nprint(&#039;Test score:&#039;, score)\n\ny_prediction = model.predict(X_test).flatten()\ny_test = y_test.values\n\nfor i in range(10):\n    real_price = y_test[i][0]\n    predicted_price = y_prediction[i]\n    print(&#039;Real Price: {:.3f}, Predicted Price: {:.3f}&#039;.format(real_price, predicted_price))<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>keras \ub97c \uc774\uc6a9\ud55c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 from keras.models import Sequential from keras.layers import Dense from sklearn.model_selection import train_test_split import pandas as pd df = pd.read_csv(&quot;\/home\/ubuntu\/workspace\/datasets\/streeteasy\/manhattan.csv&quot;) # df.head() X = df[[&#039;bedrooms&#039;, &#039;bathrooms&#039;, &#039;size_sqft&#039;, &#039;min_to_subway&#039;, &#039;floor&#039;, &#039;building_age_yrs&#039;, &#039;no_fee&#039;, &#039;has_roofdeck&#039;, &#039;has_washer_dryer&#039;, &#039;has_doorman&#039;, &#039;has_elevator&#039;, &#039;has_dishwasher&#039;, &#039;has_patio&#039;, &#039;has_gym&#039;]] y = df[[&#039;rent&#039;]] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2) model\u2026 <span class=\"read-more\"><a href=\"https:\/\/www.skyer9.pe.kr\/wordpress\/?p=462\">Read More &raquo;<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[14],"tags":[],"class_list":["post-462","post","type-post","status-publish","format-standard","hentry","category-ml"],"_links":{"self":[{"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/462","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=462"}],"version-history":[{"count":1,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/462\/revisions"}],"predecessor-version":[{"id":463,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=\/wp\/v2\/posts\/462\/revisions\/463"}],"wp:attachment":[{"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=462"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=462"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.skyer9.pe.kr\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=462"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}