YOU SAID:

A Bayesian is one who, vaguely expecting a horse, and catching a glimpse of a donkey, strongly believes he has seen a mule.

INTO JAPANESE

ベイズ法は一人、漠然と期待して、馬とロバの姿をキャッチ彼はラバを見ていると強く信じます。

BACK INTO ENGLISH

Catch a glimpse of the horses and donkeys, vaguely hoping Bayes method is one strongly believes he sees a mule.

INTO JAPANESE

馬やロバの姿をキャッチ、漠然とベイズ法が強くあることを望んで彼はラバを見ていると考えています。

BACK INTO ENGLISH

Think catch a glimpse of the horses and donkeys, vaguely Bayesian learning is strongly hoping that the he sees the Mule.

INTO JAPANESE

思うを垣間見る馬やロバ、漠然とベイズ学習は強く望んでいるラバを彼に見る。

BACK INTO ENGLISH

I think glimpse of horses and donkeys, vaguely see his Mule eager for Bayesian learning.

INTO JAPANESE

馬とロバを垣間見ることをぼんやり思うベイズ学習熱心な彼のラバを参照してください。

BACK INTO ENGLISH

See Bayesian learning avid he think vague glimpse of horse and donkey mules.

INTO JAPANESE

彼はラバの馬およびロバの漠然とした姿を考える熱心なベイズ学習を参照してください。

BACK INTO ENGLISH

He will see keen on Bayesian learning considering the vague appearance of horses mules and donkeys.

INTO JAPANESE

彼は馬のラバとロバの不明瞭を考慮したベイズに熱心に表示されます。

BACK INTO ENGLISH

He slurred horses mules and asses considered Bayesian shown in the intently.

INTO JAPANESE

彼は馬を回らないラバとロバと考えベイズに示すように、ひたすら。

BACK INTO ENGLISH

Shown to turn horses mules and donkeys and Bayesian thought he even as Hashi.

INTO JAPANESE

馬ラバとロバとベイズ橋としても考えた彼に示されています。

BACK INTO ENGLISH

He thought as the horses mules and donkeys and Bayesian bridge is shown.

INTO JAPANESE

馬ラバとロバとして考えたことやベイズ橋が表示されます。

BACK INTO ENGLISH

Thought of as horses mules and donkeys and Bayesian bridge will be shown.

INTO JAPANESE

馬ラバとロバとベイズ橋としての思想が表示されます。

BACK INTO ENGLISH

Thought as the horses mules and donkeys and Bayesian bridge will be shown.

INTO JAPANESE

考えた馬ラバとロバとベイズ橋が表示されます。

BACK INTO ENGLISH

Thought about horses mules and donkeys and Bayesian bridge will be shown.

INTO JAPANESE

馬ラバとロバとベイズ橋についての考えになります。

BACK INTO ENGLISH

Think about horses mules and donkeys and Bayesian bridge.

INTO JAPANESE

馬ラバとロバとベイズ橋について考えます。

BACK INTO ENGLISH

Think about horses mules and donkeys and Bayesian bridge.