{"id":25343,"date":"2024-10-26T09:54:17","date_gmt":"2024-10-26T09:54:17","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=25343"},"modified":"2024-11-26T08:02:06","modified_gmt":"2024-11-26T08:02:06","slug":"11-05-%eb%94%a5-%eb%9f%ac%eb%8b%9d%ec%9d%84-%ec%9d%b4%ec%9a%a9%ed%95%9c-%ec%9e%90%ec%97%b0%ec%96%b4-%ec%b2%98%eb%a6%ac-multi-kernel-1d-cnn%ec%9c%bc%eb%a1%9c-%eb%84%a4%ec%9d%b4%eb%b2%84-%ec%98%81","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/25343\/","title":{"rendered":"11-05 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac, Multi-Kernel 1D CNN\uc73c\ub85c \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0 \ubd84\ub958\ud558\uae30"},"content":{"rendered":"<p>\n    \ub525 \ub7ec\ub2dd\uc740 \ucd5c\uadfc \uba87 \ub144 \ub3d9\uc548 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP) \ubd84\uc57c\uc5d0\uc11c \ub9ce\uc740 \ud601\uc2e0\uc744 \uac00\uc838\uc654\uc2b5\ub2c8\ub2e4. \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \uc5ec\ub7ec \uac00\uc9c0 \ubc29\ubc95\uc774 \uc788\uc9c0\ub9cc, \uc774 \uae00\uc5d0\uc11c\ub294 Multi-Kernel 1D CNN\uc744 \ud65c\uc6a9\ud558\uc5ec \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0\ub97c \ubd84\ub958\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8e8\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.\n<\/p>\n<h2>1. \uc11c\ub860<\/h2>\n<p>\n    \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP)\ub294 \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud560 \uc218 \uc788\ub3c4\ub85d \ud558\ub294 \uae30\uc220\uc785\ub2c8\ub2e4. \ucd5c\uadfc\uc5d0\ub294 \ub2e4\uc591\ud55c \ub525 \ub7ec\ub2dd \ubaa8\ub378\uacfc \uae30\ubc95\uc774 NLP\uc5d0 \uc801\uc6a9\ub418\uc5b4 \ub192\uc740 \uc131\ub2a5\uc744 \ubcf4\uc774\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ud2b9\ud788, CNN(Convolutional Neural Networks)\uc740 \uc774\ubbf8\uc9c0 \ucc98\ub9ac \ubd84\uc57c\uc5d0\uc11c \ub450\uac01\uc744 \ub098\ud0c0\ub0c8\uc9c0\ub9cc, \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc5d0\uc11c\ub3c4 \ud6a8\uacfc\uc801\uc73c\ub85c \ud65c\uc6a9\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4. Multi-Kernel 1D CNN\uc740 \ub2e4\uc591\ud55c \ucee4\ub110 \ud06c\uae30\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\ucc28\uc6d0\uc801\uc778 \uc811\uadfc\uc744 \uac00\ub2a5\ud558\uac8c \ud558\uc5ec \ud14d\uc2a4\ud2b8 \ubd84\ub958 \ubb38\uc81c\uc5d0 \ub9e4\uc6b0 \uc720\uc6a9\ud569\ub2c8\ub2e4.\n<\/p>\n<h2>2. Multi-Kernel 1D CNN \uac1c\uc694<\/h2>\n<p>\n    Multi-Kernel 1D CNN\uc740 1\ucc28\uc6d0 \ub370\uc774\ud130, \uc989 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc5d0 \ucd5c\uc801\ud654\ub41c CNN \uad6c\uc870\uc785\ub2c8\ub2e4. \uc804\ud1b5\uc801\uc778 CNN\uc740 \uc774\ubbf8\uc9c0 \ub370\uc774\ud130\ub97c \ucc98\ub9ac\ud558\uae30 \uc704\ud574 \uc124\uacc4\ub418\uc5c8\uc9c0\ub9cc, \ud14d\uc2a4\ud2b8\ub97c \ucc98\ub9ac\ud560 \ub54c\ub294 \ub2e4\ub978 \uc804\ub7b5\uc774 \ud544\uc694\ud569\ub2c8\ub2e4. Multi-Kernel 1D CNN\uc740 \uc11c\ub85c \ub2e4\ub978 \ud06c\uae30\uc758 \ud544\ud130\ub97c \uc801\uc6a9\ud558\uc5ec \ub2e4\uc591\ud55c \ud06c\uae30\uc758 n-\uadf8\ub7a8(n-gram)\uc744 \ud3ec\ucc29\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n<h3>2.1 CNN\uc758 \uae30\ubcf8 \uc6d0\ub9ac<\/h3>\n<p>\n    CNN\uc740 \uc785\ub825 \ub370\uc774\ud130\ub97c \uac10\uc9c0\ud558\uae30 \uc704\ud574 \ud544\ud130\ub97c \uc0ac\uc6a9\ud558\ub294 \uc2e0\uacbd\ub9dd\uc785\ub2c8\ub2e4. \ud544\ud130\ub294 \uc785\ub825 \ub370\uc774\ud130\ub97c \uc2a4\uce94\ud558\uba70, \ud2b9\uc815 \ud328\ud134\uc774\ub098 \ud2b9\uc9d5\uc744 \ucd94\ucd9c\ud569\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc740 \uc5ec\ub7ec \uce35\uc744 \ud1b5\ud574 \uc9c4\ud589\ub418\uba70, \ucd5c\uc885\uc801\uc73c\ub85c \ucd94\ucd9c\ub41c \ud2b9\uc9d5\uc744 \uae30\ubc18\uc73c\ub85c \ubd84\ub958\ub97c \uc218\ud589\ud569\ub2c8\ub2e4.\n<\/p>\n<h3>2.2 Multi-Kernel CNN\uc758 \uc7a5\uc810<\/h3>\n<p>\n    Multi-Kernel CNN\uc740 \uc5ec\ub7ec \ud06c\uae30\uc758 \ud544\ud130\ub97c \ub3d9\uc2dc\uc5d0 \uc0ac\uc6a9\ud558\uc5ec, \ub2e4\uc591\ud55c \ud06c\uae30\uc758 \ud2b9\uc9d5\uc744 \ub3d9\uc2dc\uc5d0 \ud559\uc2b5\ud560 \uc218 \uc788\uac8c \ud569\ub2c8\ub2e4. \uc774\ub294 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\uc758 \ub2e4\uc591\ud55c \ub9e5\ub77d\uc744 \ud3ec\ucc29\ud558\ub294 \ub370 \ub9e4\uc6b0 \uc720\ub9ac\ud569\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, 3-\uadf8\ub7a8, 4-\uadf8\ub7a8, 5-\uadf8\ub7a8 \ud06c\uae30\uc758 \ud544\ud130\ub97c \uc801\uc6a9\ud568\uc73c\ub85c\uc368 \ub2e8\uc5b4\uc758 \uc870\ud569\uc744 \ud6a8\uacfc\uc801\uc73c\ub85c \ud559\uc2b5\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n<h2>3. \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0 \ub370\uc774\ud130\uc14b \uc18c\uac1c<\/h2>\n<p>\n    \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0 \ub370\uc774\ud130\uc14b\uc740 \ud55c\uad6d\uc5b4\ub85c \uc791\uc131\ub41c \uc601\ud654 \ub9ac\ubdf0\ub85c \uad6c\uc131\ub418\uc5b4 \uc788\uc73c\uba70, \uae0d\uc815\uc801 \ub610\ub294 \ubd80\uc815\uc801 \ub808\uc774\ube14\uc774 \ubd80\uc5ec\ub418\uc5b4 \uc788\uc2b5\ub2c8\ub2e4. \uc774 \ub370\uc774\ud130\uc14b\uc740 \ub525 \ub7ec\ub2dd \ubaa8\ub378\uc758 \uc131\ub2a5\uc744 \ud3c9\uac00\ud558\uae30\uc5d0 \uc801\ud569\ud558\uba70, \ud55c\uad6d\uc5b4 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uc5f0\uad6c\uc5d0 \ub110\ub9ac \uc0ac\uc6a9\ub418\uace0 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n<h3>3.1 \ub370\uc774\ud130\uc14b \uad6c\uc131<\/h3>\n<ul>\n<li><strong>\ub9ac\ubdf0 \ud14d\uc2a4\ud2b8:<\/strong> \uac01 \uc601\ud654\uc5d0 \ub300\ud55c \uc0ac\uc6a9\uc790\uc758 \ub9ac\ubdf0<\/li>\n<li><strong>\ub808\uc774\ube14:<\/strong> \uae0d\uc815\uc801(1) \ub610\ub294 \ubd80\uc815\uc801(0)<\/li>\n<\/ul>\n<h3>3.2 \ub370\uc774\ud130 \uc804\ucc98\ub9ac<\/h3>\n<p>\n    \ub370\uc774\ud130 \uc804\ucc98\ub9ac\ub294 \ub525 \ub7ec\ub2dd \ubaa8\ub378 \ud6c8\ub828\uc758 \ud544\uc218 \uacfc\uc815\uc785\ub2c8\ub2e4. \ub9ac\ubdf0 \ub370\uc774\ud130\ub294 \ubd88\ud544\uc694\ud55c \uc815\ubcf4\ub97c \uc81c\uac70\ud558\uace0, \ub2e8\uc5b4\ub97c \uc815\uc81c\ud558\uc5ec \ubaa8\ub378\uc774 \uc27d\uac8c \uc774\ud574\ud560 \uc218 \uc788\ub3c4\ub85d \ubcc0\ud658\ud574\uc57c \ud569\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \ub2e4\uc74c\uacfc \uac19\uc740 \uacfc\uc815\uc744 \ud3ec\ud568\ud569\ub2c8\ub2e4:\n<\/p>\n<ul>\n<li>\ud2b9\uc218\ubb38\uc790 \ubc0f \ubd88\uc6a9\uc5b4 \uc81c\uac70<\/li>\n<li>\ud615\ud0dc\uc18c \ubd84\uc11d \ubc0f \ub2e8\uc5b4 \ud1a0\ud070\ud654<\/li>\n<li>\uc5b4\ud718 \uc0ac\uc804 \uad6c\ucd95 \ubc0f \ud14d\uc2a4\ud2b8 \uc778\ucf54\ub529<\/li>\n<\/ul>\n<h2>4. Multi-Kernel 1D CNN \ubaa8\ub378 \uad6c\ucd95<\/h2>\n<p>\n    \uc774\uc81c Multi-Kernel 1D CNN \ubaa8\ub378\uc744 \uad6c\ucd95\ud574 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. \uc774 \uacfc\uc815\uc5d0\uc11c\ub294 TensorFlow\uc640 Keras \ub77c\uc774\ube0c\ub7ec\ub9ac\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc744 \uad6c\ud604\ud560 \uac83\uc785\ub2c8\ub2e4.\n<\/p>\n<h3>4.1 \ubaa8\ub378 \uc124\uacc4<\/h3>\n<p>\n    Multi-Kernel 1D CNN\uc758 \uae30\ubcf8 \uc544\ud0a4\ud14d\ucc98\ub294 \uc544\ub798\uc640 \uac19\uc2b5\ub2c8\ub2e4.\n<\/p>\n<pre><code>\nfrom keras.models import Model\nfrom keras.layers import Input, Conv1D, MaxPooling1D, Flatten, Dense, Dropout\n\n# \uc785\ub825 \ub808\uc774\uc5b4\ninput_layer = Input(shape=(max_length, embedding_dim))\n\n# \ub2e4\uc591\ud55c \ucee4\ub110 \ud06c\uae30\ub97c \uac00\uc9c4 Conv \ub808\uc774\uc5b4 \ucd94\uac00\nconv_blocks = []\nfor filter_size in [3, 4, 5]:\n    conv = Conv1D(filters=128, kernel_size=filter_size, activation='relu')(input_layer)\n    pool = MaxPooling1D(pool_size=2)(conv)\n    conv_blocks.append(pool)\n\n# Concatenate all the convolutional layers\nmerged = concatenate(conv_blocks, axis=1)\n\n# Flatten and add dense layers\nflat = Flatten()(merged)\ndropout = Dropout(0.5)(flat)\noutput = Dense(1, activation='sigmoid')(dropout)\n\n# \ubaa8\ub378 \uad6c\uc131\nmodel = Model(inputs=input_layer, outputs=output)\nmodel.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n<\/code><\/pre>\n<h3>4.2 \ubaa8\ub378 \ud6c8\ub828<\/h3>\n<p>\n    \ubaa8\ub378\uc744 \ud6c8\ub828\ud558\uae30 \uc704\ud574 \ud559\uc2b5 \ub370\uc774\ud130\ub97c \uc900\ube44\ud558\uace0, \uc801\uc808\ud55c \ud558\uc774\ud37c\ud30c\ub77c\ubbf8\ud130\ub97c \uc124\uc815\ud574\uc57c \ud569\ub2c8\ub2e4. \ud6c8\ub828 \uacfc\uc815\uc5d0\uc11c\ub294 \uac80\uc99d \ub370\uc774\ud130\uc14b\uc744 \ud65c\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc77c\ubc18\ud654\ub97c \ud3c9\uac00\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n<pre><code>\n# \ubaa8\ub378 \ud6c8\ub828\nhistory = model.fit(X_train, y_train, epochs=10, batch_size=64, validation_data=(X_val, y_val))\n<\/code><\/pre>\n<h2>5. \ubaa8\ub378 \ud3c9\uac00<\/h2>\n<p>\n    \ud6c8\ub828\ud55c \ubaa8\ub378\uc744 \uc0ac\uc6a9\ud558\uc5ec \ud14c\uc2a4\ud2b8 \ub370\uc774\ud130\uc14b\uc5d0 \ub300\ud55c \uc131\ub2a5\uc744 \ud3c9\uac00\ud569\ub2c8\ub2e4. \ubaa8\ub378\uc758 Precision, Recall, F1-score\uc640 \uac19\uc740 \uc9c0\ud45c\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc131\ub2a5\uc744 \ubd84\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n<\/p>\n<pre><code>\nfrom sklearn.metrics import classification_report\n\n# \ubaa8\ub378 \uc608\uce21\ny_pred = model.predict(X_test)\ny_pred_labels = (y_pred &gt; 0.5).astype(int)\n\n# \uc131\ub2a5 \ud3c9\uac00\nprint(classification_report(y_test, y_pred_labels))\n<\/code><\/pre>\n<h2>6. \uacb0\ub860<\/h2>\n<p>\n    \ubcf8 \uae00\uc5d0\uc11c\ub294 Multi-Kernel 1D CNN\uc744 \uc774\uc6a9\ud558\uc5ec \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0\ub97c \ubd84\ub958\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \uc790\uc138\ud788 \uc124\uba85\ud588\uc2b5\ub2c8\ub2e4. CNN\uc744 \ud1b5\ud55c \ubd84\ub958\ub294 \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ucc98\ub9ac\ud558\ub294 \ubc29\ubc95 \uc911 \ud558\ub098\ub85c, \ub2e4\uc591\ud55c \ubd84\uc57c\uc5d0\uc11c \ud65c\uc6a9\ud560 \uc218 \uc788\ub294 \uac00\ub2a5\uc131\uc744 \ubcf4\uc5ec\uc8fc\uace0 \uc788\uc2b5\ub2c8\ub2e4. \ub370\uc774\ud130 \uc804\ucc98\ub9ac, \ubaa8\ub378 \uc124\uacc4, \ud6c8\ub828 \ubc0f \ud3c9\uac00\uc758 \uc804 \uacfc\uc815\uc744 \uc0b4\ud3b4\ubcf4\uc558\uc73c\uba70, \ub525 \ub7ec\ub2dd \uae30\ubc18\uc758 \uc790\uc5f0\uc5b4 \ucc98\ub9ac \uae30\uc220\uc758 \ubc1c\uc804\uacfc \ud568\uaed8 \ub354\uc6b1 \ub9ce\uc740 \uc5f0\uad6c\uac00 \uc774\ub8e8\uc5b4\uc9c0\uae38 \uae30\ub300\ud569\ub2c8\ub2e4.\n<\/p>\n<h2>7. \ucc38\uace0 \ubb38\ud5cc<\/h2>\n<ul>\n<li>[1] Yoon Kim, &#8220;Convolutional Neural Networks for Sentence Classification&#8221;.<\/li>\n<li>[2] Goldberg, Y. (2016). &#8220;Neural Network Methods for Natural Language Processing&#8221;.<\/li>\n<li>[3] &#8220;Deep Learning for Natural Language Processing&#8221;.<\/li>\n<li>[4] &#8220;Understanding Convolutional Neural Networks with a Python Example&#8221;.<\/li>\n<\/ul>\n<p>\uc774\uae00\uc774 \uc5ec\ub7ec\ubd84\uaed8 \uc720\uc775\ud55c \uc815\ubcf4\uac00 \ub418\uc5c8\uae30\ub97c \ubc14\ub78d\ub2c8\ub2e4. \uc9c8\ubb38\uc774\ub098 \ud53c\ub4dc\ubc31\uc740 \ub313\uae00\ub85c \ub0a8\uaca8\uc8fc\uc138\uc694!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\ub525 \ub7ec\ub2dd\uc740 \ucd5c\uadfc \uba87 \ub144 \ub3d9\uc548 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(Natural Language Processing, NLP) \ubd84\uc57c\uc5d0\uc11c \ub9ce\uc740 \ud601\uc2e0\uc744 \uac00\uc838\uc654\uc2b5\ub2c8\ub2e4. \ud14d\uc2a4\ud2b8 \ub370\uc774\ud130\ub97c \ud6a8\uacfc\uc801\uc73c\ub85c \ucc98\ub9ac\ud560 \uc218 \uc788\ub294 \uc5ec\ub7ec \uac00\uc9c0 \ubc29\ubc95\uc774 \uc788\uc9c0\ub9cc, \uc774 \uae00\uc5d0\uc11c\ub294 Multi-Kernel 1D CNN\uc744 \ud65c\uc6a9\ud558\uc5ec \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0\ub97c \ubd84\ub958\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud574 \ub2e4\ub8e8\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4. 1. \uc11c\ub860 \uc790\uc5f0\uc5b4 \ucc98\ub9ac(NLP)\ub294 \ucef4\ud4e8\ud130\uac00 \uc778\uac04\uc758 \uc5b8\uc5b4\ub97c \uc774\ud574\ud558\uace0 \ucc98\ub9ac\ud560 \uc218 \uc788\ub3c4\ub85d \ud558\ub294 \uae30\uc220\uc785\ub2c8\ub2e4. \ucd5c\uadfc\uc5d0\ub294 \ub2e4\uc591\ud55c \ub525 &hellip; <a href=\"https:\/\/atmokpo.com\/w\/25343\/\" class=\"more-link\">\ub354 \ubcf4\uae30<span class=\"screen-reader-text\"> &#8220;11-05 \ub525 \ub7ec\ub2dd\uc744 \uc774\uc6a9\ud55c \uc790\uc5f0\uc5b4 \ucc98\ub9ac, Multi-Kernel 1D CNN\uc73c\ub85c \ub124\uc774\ubc84 \uc601\ud654 \ub9ac\ubdf0 \ubd84\ub958\ud558\uae30&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-25343","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.2 - 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