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lb_garch = stattools.q_stat(garch_resid_acf, len(close_diff_1)) | |
print(lb_garch) | |
print(lb_garch[1]) |
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from sklearn.ensemble import RandomForestClassifier | |
trainingdata = [[1, 1], [2, 2], [-1, -1], [-2, -2]] | |
traininglabel = [1, 1, -1, -1] | |
testdata = [[3, 3], [-3, -3]] | |
model = RandomForestClassifier() | |
model.fit(trainingdata, traininglabel) | |
output = model.predict(testdata) |
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# trial.swiファイル を ロード | |
['trial.swi'] | |
# 質問問いかけ 始め | |
female(alice). | |
make(ben). % 打ち間違えて、未定義の述語 make を 入力 | |
male(ben). | |
likes(alice, ben). | |
likes(ben, alice). | |
owns(ben, violin) % 未定義述語 owns を 入力 (ピリオド打ち忘れ) |
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?- [user]. | |
|: male(ben). | |
|: having_dinner(ben). | |
|: true. | |
?- having_dinner(X). | |
X = ben. | |
?- having_dinner(ben). |
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[ ["あ", "い" , "う" , "え" , "お"] , ["A", "B" , "C" , "D" , "E"] , ["ア", "イ" , "ウ" , "エ" , "オ"]] |
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[単語1のtf*id値 , 単語2のtf*id値 , 単語3のtf*id値 , 単語4のtf*id値 , 単語5のtf*id値 , ... ] |
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OCaml for the Masses - ACM Queue |
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(山下 伸夫) |
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<emotionml xmlns="http://www.w3.org/2009/10/emotionml" | |
xmlns:meta="http://www.example.com/metadata" | |
category-set="http://www.w3.org/TR/emotion-voc/xml#everyday-categories"> | |
<emotion> | |
<category name="Anger" values="0.97"/> | |
'I've got angry, Umhhhhhh !!!!!' | |
</emotion> | |
</emotionml> |
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{ | |
"canonical_mapping": { | |
"http://twitter.com/zaki": "http://twitter.com/zaki" | |
}, | |
"nodes": { | |
"http://twitter.com/zaki": { | |
"attributes": { | |
"url": "http://twitter.com/zaki", | |
"profile": "http://twitter.com/zaki", | |
"rss": "http://twitter.com/statuses/user_timeline/zaki.rss", |
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