keras approach
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@ -20,6 +20,20 @@
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"from sklearn.preprocessing import MultiLabelBinarizer"
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"from sklearn.preprocessing import MultiLabelBinarizer"
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]
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [],
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"source": [
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"# TODO importing function for sentiment to emoji mapping\n",
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"def sent2emoji(sentiment_vector: np.array):\n",
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" return '🤦'\n",
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"\n",
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"def emoji2sent(emoji: str):\n",
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" return np.zeros(3)"
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]
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},
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 2,
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@ -1263,7 +1277,7 @@
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},
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 10,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -1286,7 +1300,7 @@
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 11,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -1327,7 +1341,7 @@
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},
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},
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 12,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -1336,7 +1350,7 @@
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 13,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@ -1345,7 +1359,7 @@
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},
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},
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 14,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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