otthorn/TP_WordEmbedding
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test question

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This commit is contained in:
higepi 2022-10-04 19:23:20 +02:00
parent b6028c55bd
commit a035fe4c84
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9
wordvec.ipynb
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@ -255,6 +255,15 @@
"source": [ "source": [
"print(wv.doesnt_match(['wood', 'oak', 'tree', 'iron', 'leaf']))" "print(wv.doesnt_match(['wood', 'oak', 'tree', 'iron', 'leaf']))"
] ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print(wv.most_similar(positive=['The largest country is']))"
]
} }
], ],
"metadata": { "metadata": {

1
wordvec.py
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@ -17,3 +17,4 @@ vec_woman = wv['woman']
result = wv.most_similar(positive=(vec_father - vec_man + vec_woman), topn=1) result = wv.most_similar(positive=(vec_father - vec_man + vec_woman), topn=1)
print(result) print(result)
print(wv.most_similar(positive=['The largest country is']))